The overflow of water from a lake or river usually causes flooding. Sometimes, a dam breach might result in the unexpected release of vast quantities of water. Some of the water seeps into the ground, flooding the region. In a station, rivers are involving the riverbanks. Along with a lack of goods and houses, businesses, and offices, street infrastructure floods contain bacteria, sewage from waste sites, and chemical spills, which later cause a number of diseases. The rate of change in river stage in real time, which can assist signal the gravity and immediacy of this hazard, is a crucial piece of information for flood predictions. Understanding the type of storm that produced the moisture, including its duration, strength, and actual extent, is important for determining the possible severity of the flood. In this system, an microcontroller is connected to four separate sensors: a humidity sensor, a flow sensor, a float sensor, and an ultrasonic sensor. The float sensor detects when the water is full. With the aid of IOT, these sensor combinations are utilised to predict floods, alert the appropriate authorities, and sound an immediate alarm in adjacent communities to rapidly relay information about potential floods. These sensors provide data via the IOT’s WiFi module. When flooding conditions are detected, the system warns the nearby villages and places and estimates how long it would take for help to reach at a particular location. The technology also determines when it might be considered a flood and gives them a window of time to leave in case it does.

The objective of this study is to develop an IOT-enabled automatic vacuum cleaner using controller that can be controlled by using smartphone. This vacuum robot is capable of cleaning the entire floor of homes, rooms, and offices. In this project, controller is used as the microcontroller. Additionally, this robot is equipped with HC-SR04 ultrasonic sensors that can detect walls, obstacles, and cliffs. When there are obstacles in front of the robot, its movement will be modified according to the controller. Using these sensors, a path planning algorithm was developed to enable the robot to move and efficiently clean the entire room. With the addition of a wireless Microcontroller receiver module, the robot can be controlled wirelessly via a smartphone running the Blynk application. The user can choose between two modes of automatic cleaning, or they can control it manually. Therefore, this provides a wireless control even when the user is not at home so long as they are connected to wi-fi, and it can also be controlled automatically without the assistance of others.

The most destructive natural calamity in the world is flooding. In the event of a severe flood, it can obliterate the neighborhood and claim many lives. Billions of dollars would be spent by the government to rebuild the impacted area. In order to lower the risk of flooding, it is essential to construct a flood control system. In order to inform residents to take immediate action, such as fleeing to a safer and higher position, timely reporting on the occurrence of the flood is required. IoT-based flood warning systems are a desirable option for disaster management due to the development of Internet of Things (IoT) technology and the availability of inexpensive sensors. Flood monitoring and warning have been accomplished using a variety of IoT implementation techniques. This work provides a summary of the literature on IoT hardware implementation and the relevant solar fed flood warning system using Bolt Wi-Fi and controller tools. The paper makes a contribution by emphasizing the use of sensors, microcontroller, wireless communication, IoT platforms, and Bolt Wi-Fi embracing IoT in flood monitoring and flood warning systems. This work gives prompt feedback by giving an alert and consequently any disaster can be avoided from in its beginning phases. Also, this system utilizes solar power as a source for the overall system thereby providing power consumption and increase the efficiency of the system. The proposed technique is tested using programming instrument Proteus 8 Professional.

The digital transformation of the manufacturing industry has led to the rise of Manufacturing Execution Systems (MES) for production management. To overcome the challenge of collecting diverse data within the MES system, we developed a wireless Industrial Internet of Things (IIoT) gateway based on the Microcontroller. This gateway enables the configuration of data collection and transmission parameters through the upper computer and utilizes the S7 and MQTT protocols for data extraction, protocol conversion, and cloud integration. System testing confirms its effectiveness in wirelessly connecting and collecting data from up to 16 PLC devices, including 1200 industrial controllers.

Seniors living alone face various health and safety risks, which can often require prompt emergency assistance. Thankfully, advancements in technology have enabled several assistive devices to help monitor and support seniors living independently. In the paper a healthcare system based on IoT, mainly Bluetooth Low Energy (BLE), specifically, controller for smart nursing home is presented. The core of the system is a BLE gateway, which services three components, smart pillow for body temperature and presence, wrist-worn watch to detect fall, and a pulse sensor to measure heart rate.

This paper presents a Smart Street Lighting System using IoT technology. The project aimed to reduce energy consumption by enabling the lights to turn on only when needed. The system comprised of a Raspberry Pico-W module, LED lights, an IR sensor, an LDR sensor, Drivers, and the ThingSpeak cloud. The LDR sensor determined when it was dark enough to turn the lights on, and the IR sensor detected objects, causing the lights to shine with maximum brightness. The data generated by the system is collected and visualized on the ThingSpeak cloud. The paper discusses the system design, Implementation, and results, demonstrating the effectiveness of the IoT-enabled Smart Street Lighting System in reducing power consumption and optimizing energy usage.

In view of the recent increase in the number of colleges and universities, the university campus is more open than before, which makes it difficult for students to find seats in public places. This paper puts forward a restaurant intelligent seat finding system based on Controller to solve this kind of phenomenon. Through the combination of software and hardware of the system, using edge AI technology, cloud platform, Internet of Things platform, the function of real-time monitoring the seating situation of restaurant seats and feeding the dynamic data of real-time restaurant seating information back to the user’s through the cloud platform is realized by assisting data visualization. Through the delivery of real-time information, students can arrange meals more efficiently, and solve the problem of finding seats during meals. This work can also be applied to library, study room and other application scenes.

This work presents the development of a very user-friendly smart healthcare device for people of any age. The device is based on the IoT concept. The hardware was designed around the microcontroller development board, which processes the data acquired from four essential and well-known body sensors (temperature, pulse, oximetry, and EKG). The device can be powered from any 5V DC power supply through the micro-USB port of the microcontroller board. We implemented two operation modes for the device: an “online” one where sensor measurements are sent and stored through WiFi internet connection in a database and an “offline” mode without an internet connection where the measurements are shown only on the OLED. In both operation modes, the instructions are given step by step to the user on the OLED screen. In the case of the “online” mode of operation, we structured a database to store the measured data and represent it eloquently on a public website. In this manner, the measured data can be accessed by the end user and accredited medical personnel. Thus, doctor and patient interaction would be much tighter for better health control.

Poor airflow in buildings can cause deterioration in the health of the occupants. The health concerns may be minor occurrences such as irritation of the eyes, nose and skin, headaches and fatigue to long term effects that include respiratory disease and heart inflammation. Indoor air quality monitoring system has been touted as one of the potential applications for the Internet of Things (IoT). This paper described the design and development of an IoT-based remote monitoring device and testbed that measures indoor air quality (IAQ), specifically eCO2 level, Total Volatile Organic Compound (TVOC), temperature and humidity. Air quality sensors (BME680 and CCS811), were used with an microcontroller, which acts as the brain and sends data to the InfluxDB cloud database. The data from the IoT device are visualized and monitored through the Freeboard.io dashboard hosted on the Amazon Web Services (AWS) server. A testbed was developed at Planet IoT, The Energy Sphere, UNITEN for IAQ monitoring. A performance study was conducted to test the functionalities of the IoT devices, communications, database effectiveness, and energy requirements in terms of battery life. An insight of the IAQ in the building was obtained with the IoT device able to function both in detecting harmful gases (eCO 2 and TVOC), temperature and humidity level condition 24×7 with 76 hours of battery life for a 10 min reading interval or 273 hours of battery life for a 1-hour reading interval.

This paper presents an insight into a Wi-Fi controlled car microcontroller for car controlling. This robot can be remotely controlled even if it’s out of sight, but within the optimum range of the connection technology, Wi-Fi. The physical movement of this robot, is controlled using the L298N Motor Driver, which in turn is connected to the 2 DC motors, and the control from this motor driver, would be directed through these 2 motors to the respective wheels, thereby letting the user to control the movement of the robot. Along with this, the Cam Module would collect the visual data of the nearby close areas, and relay it back to the Wi-Fi connected device, which could be a smartphone or any such device. The base hardware on which this robot unit is made, is hard plastic which gives the unit a physical durability, and thus usable for use in rough areas like industrial sites or in underground mines for surveillance purposes.

Modern technology plays a crucial role in healthcare not only for reducing sensitive bias but also for improving transmission, documentation., and display device performance. It's veritably essential to monitor vital signs and post-operative progress. Therefore, the latest advancement in healthcare communication is utilizing the IoT (Internet of Things) technology. The Internet of Things accelerates healthcare and plays a significant role in various healthcare procedures. The current method only detects pulse rate and body temperature which doesn’t count the rate of breathing. In the proposed system, there is an advantage of counting the rate of breathing which uses as a microcontroller that acts as the bridge to connect and transfer data with multiple sensors like the heartbeat sensor. The control unit collects the data and transmits it to the network via IoT, hence furnishing Live monitoring of the patient’s healthcare Additionally, the system consists of an OLED display that continuously displays the patient's health status. The data can be viewed anytime and anywhere by the caretaker.

Plants as well as the animals are most essential in our livelihood. Plants are beneficial for the oxygen reason, balance of nature and desires of humankind. On the other hand, pets are useful to decrease pressure, tension, and loneliness. Like human beings, additionally they need water supply and food supply to survive. For forests and wild animals, the nature presents all necessary conditions to stay. But, for farming, indoor plants and pets, people must provide all essential conditions in a smart way which includes water and meals. This paper shows that it is possible to provide water to the plants and food to the pets using Microcontroller when possessors are out of their homes for an important period of time. The soil moisture sensor connected to microcontroller is used to detect the moisture level in the plant’s soil. If the obtained moisture level is below the set point, then a mobile application sends the notification to turn on the water pump so that the plant gets water supply. The servomotor connected to microcontroller controls the food dispenser to provide food to the pets. Using CAM we can monitor our pets and plants with the help of it’s live streaming feature. As a result, both the mechanisms can be activated simultaneously by creating two templates connected to the same device in the Blynk App.

In the everyday occupied work, monitoring the home patient and overseeing their state of health ceaselessly is an exceptionally troublesome task. Especially agedness person's ought to be occasionally monitored and to be educated to the doctor about their health status now and again to spare their life in critical situation. Health monitoring is the serious problem in today's world. Because of absence of appropriate health monitoring, quiet experience the ill effects of genuine medical problems. To take care of this issue, there are lot of IOT devices are there to monitor the health of patient automatically now days. A smart health monitoring system is put into practice which utilizes heart beat and blood pressure sensors associated with Raspberry Pico board to keep track the health of a patient. In the event, if a system notices any unforeseen changes in patient heartbeat and blood pressure, then it will spontaneously caution the doctor with a Short Message Service (SMS) about the patient's status with the assistance of global system for mobile communication (GSM) module and furthermore shows subtleties of heartbeat and blood pressure of patient live. On the off chance that the patient can't arrive at the clinic implies, Global Positioning System (GPS) module will assist the doctor with identifying the patient's area. In this manner, IOT based patient health tracking system effectually monitors the health status of patient and save their survives on schedule.

The aim of this paper is to develop a new energy meter which can communicate with our phones so customers can know the units consumed time-to-time, bill amount need to pay and also gives warning if the energy consumed per month crossed our predetermined value. This can simply call a smart energy meter and to develop this we need a microcontroller, sensors, Wi-Fi module with internet connection to communicate with the phone and Blynk platform to monitor units consumed and push warnings in mobile. This can simply be termed as Internet of Things (IoT). This smart energy meter also helps the electricity department to initiate prepaid recharges for the no of energy units to be used and can also initiate auto cut off power supply to the home when there are no units left in the account and the customer should recharge again to get supply back to home. This can make customers more control on their consumption and the energy can be saved and the global environment is saved.

To be sure, flooding is one of the most devastating natural calamities that needs to be addressed. It has widespread repercussions for the economy and has caused many deaths. Lack of warning causes a great deal of annual mortality. This study employed the CONTROLLER, ultrasonic sensors, and other sensors to detect and measure the depths of flood waters. Here, we measure changes in the river's level with the help of an ultrasonic HC-SR04 sensor and Raspberry Pico Microcontroller. The information after processing will be sent to the ThingSpeak IoT Cloud Platform. With this method, river levels may be tracked graphically from any location. The circuit's software was programmed using the IDE and uploaded to the microcontroller's memory. The study concluded that the proposed sensor could precisely determine the location of an incoming object and present that information as a distance on the ThingSpeak Cloud Platform. Concurrently, the sensor shows off LED indicators for your eyes to feast over. Based on data from an controller, this system uses the Internet of Things to issue warnings to the proper authorities ahead of time of any impending floods.

Women's safety is the most pressing issue in every nation today. Today, women continue to be harassed and sometimes people do not get the information they need from women to help them when they need urgent help. We all recognize the importance of women's safety. It should be, but it should be analyzed that women should be properly protected. Safety issues for women and vulnerable segments of society have drawn the attention of police and relevant authorities within and outside government. Innovative ideas are needed to address these issues, and there is growing recognition that effective use of technology can ensure safety. Therefore, this project uses pepper spray, a modern self-defense technique for women's safety. Pepper spray is developed and controlled by the Raspberry Pico itself with the help of battery. A Raspberry Pico module that can be configured to notify the user's mobile app when pepper spray is pressed. When you press the spray button, the buzzer sounds and the SOS LED lights up. Also, for women's safety she has developed two mobile applications. One for users and one for administrators. React Native is being used to create a mobile caretaker app that will help victims as soon as possible, live monitor their status, and receive mobile notifications. Share the woman's current location to the caregiver application by sharing the location via Google Maps using her mobile user application. Here's how their project can help save a woman's life and protect her in the current situation.

IoT-based smart agriculture has the potential to improve crop yields by providing farmers with real-time information about their crops and yields. This technology is beneficial because it can help farmers keep track of their farming activities, which can help them make better decisions about their crops and farming methods. The proposed system uses a soil moisture sensor to determine the moisture level of soil and then turns on or off the pump based on that information. If advances in technology make it more difficult for thieves to gain access to the farm, surveillance systems must also be updated to stay ahead of the curve. The proposed solution integrates an PIR sensor with the Microcontroller so that if motion is detected across the farm’s perimeter. Additionally, when fire or flame is detected on farmland, flame sensors will alert farm users via recorded voice, which can help to provide immediate intimation to farmers to maintain safe cultivation. These sensors are controlled by controller, and the monitored data is updated on the server.

The Internet of Things (IoT) has revolutionized the way we interact with the world around us. One of the many applications of IoT is in the field of home automation. In this project, we propose an IoT-based Circuit Breaker with Access Control using Telegram, RFID Module, Microcontroller, and Website. The circuit breaker is an essential safety device in any home or building. It protects the electrical system from overloading, short-circuiting, and other electrical faults. The traditional circuit breaker is manually operated, and it can be inconvenient to turn it on or off if you are not physically present. With the IoT-based circuit breaker, you can remotely control the power supply to your home or office. The system is designed to provide access control to authorized persons only. The user can send a message to the circuit breaker’s Microcontroller to turn on or off the power supply. The Controller receives the message, and if the user is authorized, it switches on or off the power supply. The user’s identity is verified using an RFID module that is connected to the Microcontroller. The user has to swipe the RFID card to access the power supply. The Microcontroller reads the RFID card’s unique ID and checks if it matches the authorized user’s ID. The system’s access control feature ensures that only authorized personnel can operate the circuit breaker. This is achieved through a user login system that requires a username and password. The administrator can create user accounts and assign permissions to control the circuit breaker. The system also has a web interface that allows the user to monitor and control the circuit breaker’s status. The web interface displays the current power status and allows the user to turn on or off the power supply remotely. The user can also add or remove authorized users from the system. In conclusion, an IoT-based Circuit Breaker with Access Control using RFID Module, Microcontroller, and Website is a reliable and secure way to control the power supply to your home or office. It provides access control to authorized persons only and allows remote monitoring and control of the circuit breaker’s status. This system can make your life more comfortable and safer by automating the process of controlling the power supply.

This paper presents a design and implementation of IoT based solar power monitoring system which can help remote monitoring, supervising and evaluating performance of PV module installed on roof-top or in rural Areas. Regular PV monitoring can improve the long-term reliability and give a better understanding of the overall system efficiency. Designed system for this paper has many smart features which can be added to any existing PV module system. The proposed design utilizes a Microcontroller which processes all the data and with the help of its Wi-Fi feature it sends and store data in cloud server. An IoT based monitoring with free software can help increase the effectiveness of data logging in such areas where wired telecommunication is poor.

This research work aims to design and implement a pick and place and floor cleaning robot that can operate manually via a phone application. The system includes a Microcontroller with input/output pins and a cleaning robotic arm. The robot’s actions are controlled by an controller application that works on the controller platform, enabling users to provide instructions to the robot via their phone. The robot can follow the instructions given by the user through the Android App, allowing for easy and convenient control of the robot’s movements and actions. The system’s low-cost processor makes it a cost-effective solution for home automation tasks, which can be performed by the robot. This paper describes the design and implementation of the system, along with its performance evaluation.

Neonatal incubators are essential in neonatology rooms and, as they are life support equipment, they require a maintenance frequency of at least every six months to guarantee their performance and safety. To analyze them, several devices exist designed to measure parameters such as temperature, humidity, and noise level inside the baby’s chamber. A complete analysis consists of 9 tests with a duration of 5 hours and 56 minutes overall. During this time, the workflow of the incubator is interrupted. The objective of this research is to develop an controller based prototype capable of monitoring the parameters inside the chamber; without stopping the operation of the equipment and that provides the security of not affecting the health of the premature baby. The IoT architecture was designed and the safety criteria for each component used to build the prototype were determined. Experimentation was used to perform tests in simulated environments and in a real environment. The results measured by the prototype were compared with those obtained by the certified measurement instrument Fluke INCU II. The values were compared using non-parametric statistic analysis to determine points for improvement.

The agriculture is a very important sector of Indian economy. The farming is facing various challenges present days. The main problem faced in today’s agriculture by farmers is the lack of knowledge of the requirement of the water for the crops. The farmers provide the excess amount of the water or insufficient water for the crop. In this competitive world, farmers not only depend on farming for their livelihood, but also on other occupations. Hence, there may be disturbance in watering crops. This may lead to a decrease in water levels for the crops and sometimes excess water which may also lead to damage of the crop. To get rid of this problem, smart farming system is developed using Internet of Things (IoT). Using this, the farmer comes to know about the moisture content in his field through messages that will be received. Not only just a message, in a smart agriculture system he also can water the field automatically. The main advantage of this paper is that farmers need not to spend his time to decide how much water need for specific crops. Here, moisture sensors placed in the field with the predefined quantity of the water, programmed it with a keyword moisture. When the moisture reaches or above the scale value, the motor gets automatically turned off and vice versa. A soil moisture sensor is used to calculate the moisture values in the soil and gives an input to the smart farming system, consists of Microcontroller and the data obtained from the sensor is sent to the cloud. The thingspeak is used as cloud, where the data gets stored. The proposed system also updates the information regarding the status of moisture levels regularly with messages to the owner. Later, the website is designed using thingspeak URL and the messages are displayed in the website.

This study examines how to reduce the cost of hospitals and save time using IoT components. This research study conducted a thorough investigation into the health of many parents and derived the idea to develop a system for monitoring their health. Nowadays, many individuals face health issues without receiving sufficient information about their illnesses. This study has observed various health monitoring systems and identified several loopholes that are addressed in the proposed system. Health monitoring systems employ a range of sensors, such as heartbeat sensors to measure the heart rate and temperature sensors to monitor the body temperature. Additionally, our system incorporates GPS (Global Positioning System) and ThingSpeak to determine the location and provide live monitoring on a website accessible to guardians and doctors. To enhance performance and achieve greater accuracy, this study has selected Microcontroller over controller as the primary computing component. The Microcontroller efficiently collects information from all the sensors. The primary objective of this survey is to develop an affordable health monitoring system for parents with a simple design suitable for daily use. This study also discusses about the theoretical and practical implications of the proposed model.

Due to the shortage of water resources leading to ecological damage, crop yield reduction and environmental pollution, it is important to realize remote intelligent condensation irrigation based on IoT. This paper uses IOT cloud platform, soil humidity sensor, air temperature and humidity sensor to form a remote data collection system, controller IOT cloud platform, condensation water collection equipment, optocoupler relay, solenoid water valve, ultrasonic humidifier to form an intelligent irrigation system, and photovoltaic energy generation to form a set of intelligent condensation irrigation system based on IOT. The system is based on MQTT Internet of Things communication technology, which can obtain the environmental data of the equipment in real time, use the semiconductor condensation technology to liquefy the water resources in the air, extract the water resources for irrigation in real time according to the environmental data. This intelligent irrigation system saves human and material resources, has low energy consumption, strong communication in real time, and can realize the effect of condensing water extraction for irrigation.

With the Coronavirus pandemic taking its toll all over the world, and social distancing measures being adopted, there is an urgent need to digitize all the processes for the smooth functioning of organizations. Thus, Pehchaan presents a no-contact system for recording the attendance of entities by verifying RFID. We verify the entities’ claim by comparing the similarity with the encodings stored in the database. We are using Wi-Fi networks to connect controller with the backend server. RFID and PIR together act as two-factor verification and an admin will be able to access the records of a particular day and time and thus would be able to capture the attendance without any manual effort.

This project aims to design and implement a Wi-Fi based robotic car that can be monitored and controlled remotely using an microcontroller, and various sensors. The car is equipped with a microcontroller that acts as the main control unit, a Wi-Fi module that provides connectivity to a remote device/computer, various sensors (such as ultrasonic, IR, etc.) for obstacle detection and avoidance. The remote device/computer can send commands to the car to control its movement and receive real-time data such as sensor readings, etc. The project will demonstrate the capabilities of the combination of hardware and software components to create a fully functional, autonomous Wi-Fi based robotic car.

Working women must be protected from assault in many parts of the world. A smart ID card based on the Internet of Things (IoT) could make female workers safer and be one solution to this problem. Because of the built-in sensors and connectivity components, this ID card will be able to sense and respond to its surroundings. If the sensors detect something unusual, such as a sudden movement or a loud noise, they will send a signal to the system. Following the completion of the data analysis, the system takes any necessary actions, such as sending alerts to security personnel or notifying on-call personnel. The proposed system will provide the user with access to an emergency panic button. The system’s GPS component will track the user’s location and send alerts to the appropriate parties. There will also be a cloud-based monitoring system with the proposed approach. This allows the employer or loved ones of the worker to track the worker’s whereabouts and activities in real time. The system will analyze the data using machine learning techniques, and the results will reveal the worker’s behavior and level of safety. A smart ID card linked to the Internet of Things (IoT) could help women work in safer environments. The proposed technology would enable real-time monitoring, predictive alarms, and data analysis. All of these precautions will help ensure female employees’ safety and avoid unpleasant situations.

The toxic gases emitted from garbage waste in houses or communities harm the environment and human health. Various health issues, such as respiratory problems and skin cancer, will occur because of these toxic gases. Considering such cases, it aims to develop a sensor-based system to detect the presence of ammonia, hydrogen sulfide, methane, humidity, temperature, and garbage level in the bin. The data acquisition and processing units collect and analyze the sensor data, generating real-time gas concentration readings. Hypertext processors and controller programs are used to obtain and monitor the readings of the sensors. Moreover, an exhaust fan is placed, which turns on when the gas levels or the temperature increases above respective threshold values.

Goal of this paper is to provide an implementation model for detecting electrical energy theft without involving humans. This framework’s goal is to decrease instances of energy theft and mishaps that result from it. It has a Raspberry Pico-W Board, which is an entirely hardware kit-based embedded technology and wireless communication technique to identify distribution line faults and electrical theft. A IoT prototyping platform is Raspberry Pico-W. The Raspberry Pico-W Board has many benefits, including remote programming, simple code transfer, and quick project turn-on. The primary features of this are its quick processor, ample memory, and built-in WiFi. The proposed system will be effective and a viable alternative to embedded and controller-based data processing.

In present times safety and security of students is a major concern to the parents and the school administrations. In this concern, many technologies are rapidly evolving that provides many real time methodologies. This paper assists a solution by providing a real time monitoring of school bus and security systems using IOT, by which parents can have a track on their children’s location and availability. Obstacle detection and acceleration monitoring is also done using ultrasonic sensors and accelerometer. When a student gets in a bus, the fingerprint verification is done using the fingerprint module which ensures only authorized students enter the bus. The collected information from sensors is updated in a real time web server, where the location of the bus and sensor values are displayed. so that parents and the administration can track the current location of the bus using a website developed. The system will sound an alarm and alert the school administration and parents if any sensor values surpass a typical threshold. A DC motor will also be a part of the system to manage the speed of the bus and a buzzer will notify the driver of any unusual sensor readings. An alert message will also be sent.

This paper deals with proper monitoring and controlling of energy consumption as well as detecting the power theft if anyone is trying to theft the electricity. Nowadays, lots of energy gets wasted due to thefts and consumer has to wait for the person to come from utility to provide them with the energy meter bill. An Internet of Things (IoT) and controller-based smart energy meter is suggested as a solution to these issues. The Raspberry Pico used in this project is controlling the power theft if anyone tries to theft electricity. With the implementation of IoT, which is required Raspberry Pico i.e., not only controlling the loads which are connected to a 4xl channel relay but also providing the details of energy consumption to IoT interface so that information can be used by the consumer.

IoT based poultry cultivating is valuable in circumstances where remote checking and upkeep is required and this changes the regular homestead into a cutting edge ranch with different mechanized highlights. Different variables that influence the strength of chicken are checked consistently at span to further develop wellbeing and development of chicken. This paper gives an understanding on the most proficient method to arrange an IoT based Smart Poultry Farming System utilizing IoT parts. The framework involves Microcontroller for communicating with various sensors to detect the upsides of explicit boundaries and microcontroller Wi-Fi Module to transfer the information to the cloud. Various ecological elements are detected in the poultry executive framework, which incorporates temperature, smelling salts content in the air and light power. The framework screens these boundaries, yet in addition manages them really with the assistance of different mechanized methods. The proposed work is valuable to ranchers who follow regular cultivating strategies as they could do without much of a stretch access and control the poultry ranch remotely utilizing their cell phones in this way diminishing the manual checking and expanding the yield of the poultry ranch.

This study concentrated on low-cost greenhouse environmental monitoring systems for intelligent farms. A small greenhouse that uses data comparison to autonomously manage the greenhouse's climate and the growth conditions of planted plants is built. The Microcontroller, a cheap microcontroller and environmental management sensors are used. It was able to verify the energy-saving effect since the grid-type solar power system was built as a way to maximize energy efficiency during the study phase.

Every year, many resources are lost and animal life is in danger due to railroad accidents. To prevent the entry of wild animals near railroad tracks, they have to be monitored all the time. In this project, we propose a system that will monitor a railroad track for humans and animals. For the first round of surveillance, we have a PIR sensor for motion detection, a MEMS sensor for vibration. Both data-driven Intelligent Transportation Systems (ITS) and the nascent Internet of Vehicles (IoV) services, like railroad barrier tracking at railroad crossings, railroad warnings, and light signaling systems, have the potential to be considerably improved by the use of IoT-based solutions. The train is the most well-liked and environmentally sustainable mode of transportation in the biggest cities on earth. For a convenient, secure, and affordable travel option, the train is the most popular. It is affordable to people in various vocations. One of the most effective ways to prevent train accidents is the subject of this project, which uses an Microcontroller to create a multi-sensor railway track geometry surveying system. All the sensors are controlled, and information is transmitted and received. It can prevent accidents and safeguard animals and people. This system continuously monitors the status of the track and updates its time and its information to the IoT cloud platform, known as Thing speak. This information is observed in the mail or on the mobile phones of nearby railway officers so that they can take immediate action in order to prevent railway accidents.

Health monitoring systems have achieved great popularity and great importance, especially with the presence of pandemics, large numbers of patients, and a lack of health staff. The presence of sensors on the patient's body to measure blood pressure, body temperature, and heart rate, in addition to room temperature and humidity, constantly supports the specialized medical staff in measuring these indicators. The advantage of these devices is that they are with the patient all the time, and a nurse cannot accompany a patient for this period. In this paper, a health care system is designed and implemented to measure vital signs and room environment temperature and humidity. Controller receives the vital signs data from the patient and his room. This information has been sent to the Raspberry Pi pico where the information was compared to the information provided by the doctor to ensure obtaining the alarm when the measure has a large difference. The system obtains two types of alarms; the first is a medical alarm that accrues when vital signs are high or low from the normal measurements. This alarm calls the medical staff, while the second alarm occurs during a hardware malfunction. The second type of alarm call the technical staff. Testing the system shows that the two types of alarm have been recognized on their occurrence. All these measurements and alarms have been stored in the cloud for patient health monitoring.

Internet of Things (IoT) based smart farming and irrigation systems can automate the watering of plants, which can lead to increased irrigation efficiency, decreased water waste, and increased agricultural yields. Additionally, these systems can reduce physical labor and enable senior individuals to participate in farming. This article studies the usage of IoT-based intelligent agricultural and irrigation systems that automate the watering of plants. The study employs multiple sensors including soil moisture, DHT11 to monitor numerous plant characteristics such as humidity, wetness and temperature in order to ensure that plants are appropriately hydrated. The system also includes an Microcontroller module, a relay module, a water pump. The technology intends to increase irrigation efficiency while decreasing water waste, which would ultimately result in increased agricultural yields and decreased expenses for farmers. In addition, this technology considerably minimizes physical labor and encourages farming with ease. This research concludes by highlighting the substantial benefits of IoT-based smart farming and irrigation systems. By automating the process of watering plants and monitoring important plant characteristics, farmers may cultivate healthy crops with less work, decreased expenses and higher productivity.

Smart city is a term that can be described as technology that promotes sustainable development practices. Due to inefficient design, most street lighting nowadays wastes a lot of electricity. A smart city’s key aims in streetlight management are energy economy and simplicity of maintenance with little manual labour. This research has designed an intelligent street lighting system that incorporates an automatic control mechanism for energy savings. The light intensity, the Wi-Fi network and the status of the streetlights were designed and monitored. An microcontroller was used to process the sensor values and controls the output devices from the motion sensors and Light-Dependent-Resistor (LDR) sensors. The controller and sensors are powered by their Photovoltaic (PV) system. The solar panel is connected to TP4056 which acts as a charge controller for the Li-ion battery. The result has identified that the low-dropout (LDO) regulator power achieved consumption is 4mA. The clock speed of the controller is reduced from 240Mhz to 80Mhz in reducing the power consumption. There is no performance issue was observed with the reduced clock speed. The use of light-emitting diode (LED) as the light bulb and controlled brightness provides lower power consumption of about 63.5% for 11 hours of usage. The use of solar power shows that street lighting is no longer needed to connect to the grid, and it is significant compared to conventional street lighting which consumes a lot of energy and requires a high cost of maintenance.

This paper presents the Design and Development of IoT Based Weather and Air Quality Monitoring stations that provide weather-related information for agriculture, and aviation climate forecasting purposes. The prototype is made up of an outdoor unit that consistently monitors numerous climatic variables such as temperature, humidity, rainfall, and air quality using sensors with high accuracy. The air quality index(AQI) is also calculated using the sensors values which tell us whether the atmosphere is safe or polluted. Microcontroller which has a WiFi module is used to gather and send the sensor data through the Internet of things (IoT) to a ThingSpeak channel (IoT cloud), an internet platform where the data is saved, analyzed and read the data remotely. The weather station makes use of photovoltaic power and a rechargeable lead-acid battery to sustain the system. This paper also discusses the obvious strengths and shortcomings of the system and suggests plausible upgrades to assist the system in obtaining higher and long-term performance.

In recent times, the energy calibration methods are universally expanding with the goal of effectuating, reliably operating, and managing the utility system. The growing demand for power in the current environment has necessitated the mandatory installation of energy meters, as well as the development of new methods for calibrating meter readings and governing the effective use of energy resources. AMR (Automatic Meter Reading system) is one such modernization. This employs analogue or digital energy meters with the assistance of smart meters. Currently, energy scaling is done by hand, which is a time-consuming process in the world of day-to-day networking demand and also requires skilled labour. The concept of AMR Systems is to overcome complexities in the rapidly growing field of energy management. This article proposes a smart energy meter based on IoT to detect the power theft. The proposed model consists of Microcontroller, current sensors, and so on. The current sensors senses current usage with the help of the microcontroller, which is then passed to the IoT platform. Though AMR is a very effective method, it costs the proxy of existing energy meters by SEM (Smart energy meters), which is highly inefficient. As a result, the proposed method focuses on detecting the power theft caused by public tampering. The proposed model is programmed by using a software and simulated in PROTEUS software. The proposed system is then validated by using the simulated results.

India is a country that focuses on raising crops. The agricultural understanding was everything to our ancient populations. The majority of Indians depend on agriculture for their daily needs, and it has a significant impact on the nation's economy. Irrigation becomes challenging in dry areas or cases of little rainfall. To provide the best results and safeguard farmers, it must be forced upon them. A substantial role is played by horticulture, a subsector of agriculture, in the economy, human nutrition, gender mainstreaming, and employment. Fruits, vegetables, flowers, spices, and sauces are examples of horticultural goods, which have continuously increased and now make up a significant portion of the agricultural trade. The purpose of the automatic irrigation control system is to decrease the efforts of the human operator (gardener) in horticulture operations. The goal of the horticulture system is to maintain measures of food security. Farmlands have historically had their soil moisture levels checked manually. This is frequently time-consuming and ineffective, thus a method that is effective at regulating and keeping track of soil moisture levels is required. To communicate data from the board to the user's smartphone or laptop, this study presents an Internet of Things (IoT)-based soil moisture monitor that uses Microcontroller with an integrated Wi-Fi module to monitor soil moisture level. The soil moisture monitors measure the amount of water in the soil and notify the farmer when the moisture sensor's predetermined threshold rate rises or falls, indicating overwatering or underwatering, respectively. This control system is based on an controller that has been coded in embedded C. Data from the sensor is also transmitted during this procedure, first to the cloud and subsequently to the database server. By ensuring that water is not wasted, the proposed soil moisture monitor's evaluation utilizing Thing Speak.

Health monitoring system in general is an innovation which is adopted worldwide especially in the last decade. The Patients suffering from permanent disables are much required to monitor them for their survival. Such patients are facing lot of issues because in no time their health is at risk. It is very difficult to predict them as there is a need of nursing all the time too. This paper presents a mobile phone linked health monitoring device programmed and controlled by Internet of Things (IoT). The important takeaway is to provide a handheld support for the healthcare professionals can monitor or to be notified when they are even outside the hospital environment to ensure the safety of the disable patients. The sensors collect the necessary information which is been sent to the IoT server and linked with the Internet module. The system consists of sensory devices, data acquisition system (DAQ), a controller and a software application. The body temperature, heat rate per minute are constantly monitored and stored as a report. The same report has been sent to the professionals, mobile phone through developed IoT application. Additionally, a text message is sent to the senior doctors' mobile phone if the sensor data exceeds the threshold value. Therefore, a mobile phone linked health monitoring system for disable patients constantly monitor and notify the concerned person on time and save precious life.

This paper presents the solar powered smart water monitoring system using IoT. Water is an important and free natural resource that humans require on a regular basis. Maintaining water cleanliness is important and our shared duty. Most infections illnesses, which result in millions of deaths each year, are brought on by contaminated water. The purpose of this study is to analyze the water quality of Melor river in Kelantan and to develop a solar-powered Internet of Things (IoT) based water quality monitoring system. The device is powered by a solar array which deployed with three sensors that are turbidity, and total dissolved solids sensors. The water’s parameter data has been sent to a data center in real time using an microprocessor and sensors. Data on water quality can be monitored using a Blynk application on a smartphone through IoT development. The result presents the analysis which shows 34 hours for the battery to completely charge in a solar-powered system. The findings indicate that the neighborhood’s river’s water condition was suitable based on the water’s TDS content readings which is below 300 ppm. The pH measurement was good within the zone of 4-11 and the water was also identified as cloudy.

Nowadays, women’s safety has emerged as one of the world’s most pressing issues, and crime against women has significantly increased nationwide. The frequency of auto theft and accidents has increased significantly as compared to the previous decade. The value of a human life exceeds all other values, and it is more crucial to seek assistance when you do so than to provide a helping hand. Every day, women from all walks of life struggle to maintain their safety and defend themselves. In the presence of insensitive guys who regularly harass, assault, and violate the dignity of women, and in front of their wandering eyes. Public transport, especially public places, has become hunter territory. For these atrocities that women undergo current scenario A clever wearable safety tool for girls primarily based totally at the Internet of Things is being implemented. It consists of a Arduino and a buzzer, and a button to activate the service. This unit is very remote and with the click of a button, it is activated by the victim when attacked, retrieves their current location. A predetermined Application will receive notifies the location. It monitors through the victim’s smartphone and avoids the usage of additional hardware or modules, keeping the device compact. Live Position is obtained by GPS module There are numerous initiatives being taken with the goal of saving lives. The proposed study intends to develop an IoT-based security system that priorities protecting women.

In recent times, the energy calibration methods are universally expanding with the goal of effectuating, reliably operating, and managing the utility system. The growing demand for power in the current environment has necessitated the mandatory installation of energy meters, as well as the development of new methods for calibrating meter readings and governing the effective use of energy resources. AMR (Automatic Meter Reading system) is one such modernization. This employs analogue or digital energy meters with the assistance of smart meters. Currently, energy scaling is done by hand, which is a time-consuming process in the world of day-to-day networking demand and also requires skilled labour. The concept of AMR Systems is to overcome complexities in the rapidly growing field of energy management. This article proposes a smart energy meter based on IoT to detect the power theft. The proposed model consists of Microcontroller, current sensors, and so on. The current sensor senses current usage with the help of the Microcontroller, which is then passed to the IoT platform. Though AMR is a very effective method, it costs the proxy of existing energy meters by SEM (Smart energy meters), which is highly inefficient. As a result, the proposed method focuses on detecting the power theft caused by public tampering. The proposed model is programmed by using a BLYNK software and simulated in PROTEUS software. The proposed system is then validated by using the simulated results.

In India During the second wave of Covid-19 Pandemic almost all towns and cities hospitals beds where fully occupied and the entire health department has collapsed with lot of issues. The issues faced by the ambulance drivers who take the patients to the hospital had waited outside the hospital for a prolonged time due to the unavailability of Beds, Ventilators, Medical ICU and lack of oxygen supply leads the patients to die inside the ambulance itself which parked in front of the hospital make the death ratio to all-time high. The major issues we faced during the second wave is we don’t have a proper system connecting to all hospitals nearby to identify which hospital is having beds, Ventilator availability, Medical ICU availability and so on, and at the same time by checking the parameters of patients in Ambulance, decisions cannot be taken on right time for the Ambulance person which hospital is having the availability of necessary Medical system, In order to avoid such situations we are having a proposed system in that all hospital choosing decision will be made by Controller Board by fetching the details from the hospital availability and medical system availability from the centralized server page connecting to all hospitals nearby. The Controller board will take all the bio medical parameters of Patient like Spo2, HB, respiratory and body temperature and it’ll process with the algorithm, and decide the patient falls under which categories he needs like oxygen bed support, ventilator support, and MICU support by checking with the networked medical system availability hospital using IoT. If a critical patient lost his conscious it’s difficult for the entire family to Track their dear ones taken to an ambulance and going to which hospital after searching the necessary Medical system availability. So Controller board will Keeps ambulance details, selected hospital details, patient details and it will post in Local Hospital Telegram Community channel which that family member can join easily. This Thingspeak Channel posting will help to reduce the Corruptions in hospitals by denying the availability of Medical systems for quoting high to richest person which will deny treatment to the poor simultaneously corruption of ambulance drivers for diverting the patients to the hospital, which pay him bribe.

Cognitive impairment diseases are becoming more and more prevalent mainly due to population aging and the increase in life expectancy. Sensory and monitoring systems may allow people with mild cognitive impairments (MCIs) or at early stages of dementia to live at home for longer with more independence and security. This work presents a wireless sensor network (WSN) based on wearables that obtains indoor and outdoor location and step information, reporting them over a long-range WAN (LoRaWAN) network. Each wireless wearable sensor (WWS) uses a global navigation satellite system (GNSS) module for outdoor positioning, a proposed indoor room-level localization system based on infrared sensors, an accelerometer for a step detector algorithm, and a long-range (LoRa) radio link to send the measured information with low-power consumption achieving a large coverage range. These sensory data are recorded in a database and presented to the medical services and caregivers through a user web application. This can be used to detect anomalous changes in daily patients’ routines, as well as to know the user’s position in cases where the patient may be disoriented. In addition, alerts are launched in caregivers’ smartphones to report about any risky situation, such as the patient leaving an allowed area or staying in one place for too long. Therefore, the proposed sensory system may support and extend the ability of people with MCI or at early stages of dementia to live independently, it helps detect behavioral changes and it keeps caregivers’ peace of mind.

Recent developments in IoT-enabled cloud computing and interactive applications have made researchers rethink how healthcare services are currently provided. The IoT-cloud-based systems facilitate remote monitoring and support for patients. However, in the existing area, much emphasis has not been given to making the healthcare systems green. So, in this paper, we present an integrated framework for green healthcare and use cutting-edge technology to make an interactive user interface. We have also ensured the system’s scalability and performance ratio. This system interface has been designed and developed for patients and doctors, where patients can send their healthcare data using wearable sensors, and doctors can receive those data in real-time. For data identification and analysis, we have adopted Hierarchical Clustering Algorithms. Finally, we have come up with a solution for how to make the interactive healthcare experience better for everyone.

Technologies like AI and IoT have been employed in farming for some time now, along with other forms of cutting-edge computer science. There has been a shift in recent years toward thinking about how to put this new technology to use. Agriculture has provided a large portion of humanity’s sustenance for thousands of years, with its most notable contribution being the widespread use of effective agricultural practices for several crop types. The advent of cutting-edge IoT know-how with the ability to monitor agricultural ecosystems and guarantee high-quality production is underway. Smart Sustainable Agriculture continues to face formidable hurdles due to the widespread dispersion of agricultural procedures, such as the deployment and administration of IoT and AI devices, the sharing of data and administration, interoperability, and the analysis and storage of enormous data quantities. This work initially analyses existing Internet of-Things technologies used in Smart Sustainable Agriculture (SSA) to discover architectural components that might facilitate the development of SSA platforms. This paper examines the state of research and development in SSA, pays attention to the current form of information, and proposes an Internet of Things (IoT) and artificial intelligence (AI) framework

Ladies security has emerged as one of the most important needs in our nation, taking into account what is happening in the metro metropolitan neighbourhood’s and other big urban locations. A simple safety gadget that aids victims in the event of unforeseen danger is essential in this era of cutting-edge technology and smart devices. This study provides a detailed description of the design and implementation of a prototype for an electronic device that could, in the future, function as a safety wear. These days many women, young girls & mothers are seen vanishing from public spaces, streets, and public transit and they face physical and sexual abuse. Most lawsuits are routinely lodged on issues like abduction, intimidation, or assaults and these crimes are rising day by day. To stop these crimes, an embedded system-based Women Safety Night Patrolling IoT Robot is designed for street surveillance to monitor a live update to the control room during nighttime. This also comes with a unique alarm feature that gets triggered when it receives an abnormal level of sound from the environment (these things don’t happen quite usually). This night patrolling robot notifies society’s people whenever a woman shouts for rescue. This prototype is predefined to patrol the street at night time. Two robots are installed for a road, and the primary purpose of this project is to ensure public safety in emergencies.

Powered by IoT technologies, smart home systems effectively support aging-in-place. However, they have some limitations in comprehensive event perception and timely appropriate action. Homecare robot systems have been proven to be effective in homecare task executions but still have significant technological challenges. To address this problem, this paper proposes a smart home system architecture integrating a mobile robot with better event perception and task execution performance. To support the proposed system architecture, an ontology of the smart home is built to address the data heterogeneity issue. Then an event perception method is built upon multi-data integration. To perform complex tasks, this work implements an improved genetic algorithm for task planning. Finally, simulations and physical experiments are conducted to validate the feasibility of the proposed system architecture.

WiFi sensing has received recent and significant interest from academia, industry, healthcare professionals, and other caregivers (including family members) as a potential mechanism to monitor our aging population at a distance without deploying devices on users’ bodies. In particular, these methods have the potential to detect critical events such as falls, sleep disturbances, wandering behavior, respiratory disorders, and abnormal cardiac activity experienced by vulnerable people. The interest in such WiFi-based sensing systems arises from practical advantages including its ease of operation indoors as well as ready compliance from monitored individuals. Unlike other sensing methods, such as wearables, camera-based imaging, and acoustic-based solutions, WiFi technology is easy to implement and unobtrusive. This paper reviews the current state-of-the-art research on collecting and analyzing channel state information extracted using ubiquitous WiFi signals, describing a range of healthcare applications and identifying a series of open research challenges, including untapped areas of research and related trends. This work aims to provide an overarching view in understanding the technology and discusses its use-cases from a perspective that considers hardware, advanced signal processing, and data acquisition.

Machine learning (ML) provides effective solutions to develop efficient intrusion detection system (IDS) for various environments. In the present paper, a diversified study of various ensemble machine learning (ML) algorithms has been carried out to propose design of an effective and time-efficient IDS for Internet of Things (IoT) enabled environment. In this paper, data captured from network traffic and real-time sensors of the IoT-enabled smart environment has been analyzed to classify and predict various types of network attacks. The performance of Logistic Regression, Random Forest, Extreme Gradient Boosting, and Light Gradient Boosting Machine classifiers have been benchmarked using an open-source largely imbalanced dataset ‘DS2OS’ that consists of ‘normal’ and ‘anomalous’ network traffic. An intrusion detection model ‘‘LGB-IDS’’ has been proposed using the LGBM library of ML after validating its superiority over other algorithms using ensemble techniques and on the basis of majority voting. The performance of the proposed intrusion detection system is suitably validated using certain performance metrics of machine learning such as train and test accuracy, time efficiency, error-rate, true-positive rate (TPR), and false-negative rate (FNR). The experimental results reveal that XGB and LGBM have almost equal accuracy, but the time efficiency of LGBM is much better than RF, and XGB classifiers. The main objective of the present paper is to propose a design of an efficient intrusion detection model with high accuracy, better time efficiency, and reduced false alarm rate. The experimental results show that the proposed model achieves an accuracy of 99.92% and the time efficiency comes to be much higher than other prevalent algorithms-based models. The threat detection rate is greater than 90% and less than 100%. Time complexity of LGBM is also very much low as compared to other ML algorithms.

Internet of Things (IoT) technology is a complementary part of our style of life. IoT technology coexists with existing cellular communication for developing 5G. Both academic researchers and industrial householders pay attention to the benefits of IoT technology. However, the rapid growth of IoT networks suffers from some limitations, such as heavy traffic load, traffic congestion,. . . etc. In this paper, a parallel distributed smart home architecture is proposed to solve human-being problems and achieve welfare in society. The proposed network has a light traffic load and low traffic congestion to avoid a single-point failure. The architecture of the proposed smart home network involves connectivity, security, registration, protocols, and scenarios to update registration. Also, the paper presents a framework of state diagrams, processes, and algorithms for IoT smart home networks. This framework includes a design and implementation of a pilot model of IoT smart home domains to meet human beneficiaries. The model consists of six practical smart home network domains in both normal and urgent modes to proof of the concept. The pilot model is programmed based on three major aspects: objectives, processes with algorithms, and state diagrams. The novelty of the paper lies in the capability to implement a smart home architecture pilot model using simple development kits. The design and implementation of the practical IoT smart home networks are tested and measured using a CoolTerm sniffer tool. The results of measurement prove that the proposed model achieves light traffic profiles and low average data rates.

Systems with voice control are an attractive option for increasing technological integration, not only for people with little knowledge on technology or constrained Internet access, but also for people with certain disabilities. In addition, devices based on Alexa or Google Home provide an interesting alternative for interacting with Internet of Things (IoT) devices, but they usually rely on an Internet connection to a cloud server for their full operation. Furthermore, many voice-recognition systems are only available in a limited number of languages, which tend to be those with the highest number of speakers, thus excluding minority-language speakers. To address the previously mentioned issues, this article presents a solution based on Edge Computing and voice commands that carries out offline voice processing and that is able to interact with IoT-based systems. The proposed system performs local speech inference, providing a communication interface with IoT devices in a Bluetooth mesh, all in a fast way and without the need for an Internet connection. In addition, the proposed solution can be adapted easily for voice recognition of languages with few resources. Such a feature is demonstrated with the Galician language, which is spoken by less than 3 million people worldwide. In particular, different Automatic Speech Recognition (ASR) models based on three of the most popular ASR development frameworks (wav2vec2, DistilHubert, Whisper) were developed to transcribe short speech and to translate it into IoT commands that perform specific home automation actions. Such models were fine-tuned for Galician with a corpus of approximately 20 hours and were evaluated in static and mobile opportunistic scenarios in terms of accuracy, energy consumption and latency on an embedded platform (that acts as an edge device) and on a cloud server. The obtained results show that inference is performed in less than 2 seconds on a Raspberry Pi 4 for the two smallest models and in less than 500 ms on a high-end Android smartphone when processing all data locally with CPU-only inference (i.e., without hardware acceleration or external processing). The results of the transcriptions are accurate enough to be able to use simple text distance algorithms to detect keywords in the speech and perform commands on IoT devices. In particular, a maximum success rate of 92% was achieved for detecting the indicated commands when using models optimized for being executed on embedded devices. For selected home scenarios, command actions were sent via Bluetooth with average response times of up to 113 ms.

Fire alarms and monitoring systems presented by the Internet of Things (IoT) are ideal for commercial and residential applications. Fire is the main factor in incidents that result in significant loss of life and property. The Microcontroller Wi-Fi module and the internet of things (IoT) make monitoring and controlling fire occurrences simple and dependable. The present research looks at the current systems for fire detection and prevention. Designing and creating a splitting protection warning system for fire detection and prevention in industries using reducing technologies like the internet of things. This proposed system integrates the Internet of Things (IoT) with fire detection and tracking systems. It can detect gas, temperature, flame, etc., and send that information to an microcontroller Wi-Fi module, providing prevention guidelines for employees or end users. In the design prototype, sensors are positioned in three places to pinpoint any fire threats’ precise location. The controller coupled to all of these sensors continuously receives input from them. The controller constantly processes these data.

Hydroponics is a farming method that makes efficient use of both space and land. Growing plants hydroponically requires consideration of pH, nutrition, water regulation, and light sources. The latter two can be managed using pumps and light-emitting diodes (LEDs), respectively; which require electrical energy. This research investigated hydroponics and electrical energy consumption concerns for prototype design, implementation, testing, and analysis with a framework of fuzzy logic and the Internet of Things (IoT). This work employed BH1750, SEN0244 TDS, PH-4502C, ACS712, and 170640 sensors for temperature, illuminance, nutrition, pH, electric current, and voltage sensing, respectively. The control parts were an microcontroller board, and DS3231 RTC, and the output parts were the growing light LEDs, LCD, DC water, and peristaltic pumps. Swamp cabbage plant samples were utilized for three comparative prototypes: fuzzy-based, schedule-based, and natural methods. The testing was conducted for 36 days. The results showed that the typical plant height difference between the fuzzy-based and natural methods was 1.75 cm (26.3%) and that of the schedule-based and natural methods was 1.28 cm (22.8%). Furthermore, the typical plant growth rates were 0.50 cm/day, 0.44 cm/day, and 0.32 cm/day for the fuzzy-based, schedule-based, and natural methods, respectively. Moreover, consumed energy savings with the fuzzy-based versus schedule-based methods was 49.11 Wh (4.75%), 49.02 Wh (4.75%), or 48.99 Wh (4.74%) using ordinary, Simpson’s composite rule, or trapezoidal composite rule computation methods, respectively. The fuzzy-based method undoubtedly increased the plant’s height and growth rate, while requiring energy consumption that was less than that of the schedule-based method.

The exponential growth in road accidents has led to a need for continuous driver monitoring to enhance road safety. Existing techniques rely on vehicle sensor-based and behavior analysis-based approaches, where the behavior analysis-based approaches are generally considered more desirable as they enable reliable detection of a more elaborate set of driver behaviors. They are categorized as intrusive and non-intrusive approaches. Unlike intrusive approaches that generally rely on constant direct human contact with sensors (physiological signals) and are sensitive to artifacts, non-intrusive approaches offer a more effective behavior monitoring using computer vision-based techniques. This paper proposes an end-to-end non-intrusive IoT-based automated framework to monitor driver behaviors, designed specifically for logistic and public transport applications. It consists of an embedded system, edge computing and cloud computing modules, and a mobile phone application, in an attempt to provide a holistic unified solution for drowsiness detection, monitoring, as well as evaluation of drivers. Drowsiness detection is based on detecting sleeping, yawning, and distraction behaviors using an image processing-based technique. To minimize the effects of latency, throughput, and packet losses, edge computing is performed using commercial off-the-shelf embedded boards. Moreover, a cloud-hosted real-time database for remote monitoring on interactive Android mobile application has been set up, where admin can add multiple drivers to get drowsiness notifications along with other useful related information for driver evaluation. An extensive experimental testing has been performed, obtaining encouraging results. An overall accuracy of 96% is achieved along with an enhanced robustness, portability, and usability of the proposed framework.

Water is a major preoccupation for our generation since it is crucial in keeping a healthy ecosystem and supporting biodiversity. The state of aquatic systems and water bodies needs to be continuously monitored to make informed decisions and trigger sanitation when necessary. However, observing and tracking the evolution of many water bodies without disturbing and polluting the biotopes is expensive, not scalable, and thus, infeasible. This article presents a way to make sustainable measurements using a new low-cost, open-source, and autonomous monitoring system deployable in a broad network. The smart buoy is deployed and controlled by a central unit that uses lab-graded sensors to measure ambient factors. The custom electronic board offers sustainable electronics integration emphasizing power path and network connectivity. The smart buoy showed an average power consumption of 1.8 mA and a cost of 932 euros per device. Currently, five spots have been monitored, which allowed the understanding of why biological events, such as a massive fish death, occurred. The system is easily expandable and can be used in various applications to increase the knowledge of the underwater ecosystem.

Electric energy prediction is an important issue and has been studied for many years. The prediction approaches have evolved from traditional statistical methods, conventional machine learning methods, deep learning (DL) methods, and then hybrid deep learning methods. This article proposes Electricity Talk, an Internet of Things (IoT) platform for smart farms, which integrates the artificial intelligence (AI) mechanism with farming IoT devices for electric energy prediction and anomaly detection. The AI mechanism called AI talk is designed with modified convolution neural network (CNN) and long short-term memory models. Traditional electric energy prediction approaches only consider the information provided by smart meters. This article shows that with the extra IoT switch status information in the smart farm and postprocessing with a simple yet novel random walk model, the performance of Electricity Talk is significantly improved (by 34.5%) as compared with the AI mechanism without the farming IoT switch information. We show that the mean absolute percentage error of AI talk is 8.62% (for the UCI dataset) and 1.53% (for the Bao farm dataset), which outperforms the previous solutions. We also show that ElectricityTalk detects all anomalies in real farm operations, and can achieve recall of 1 and precision larger than 0.994, which also outperforms the previous solutions. In particular, our mechanism can detect all anomalies in three minutes, which has not been reported in previous studies.

Modern society needs bathrooms. Poor sanitation is caused by worn-out appliances and expensive cleaning. The technique also requires an inexpensive, dependable sensor. This study had three goals. Creating an IoT administration platform is the main goal. Literature evaluations assess the merits and downsides of existing systems. Second, we suggest predictive maintenance to assist predict bathroom equipment breakdowns. Finally, a scheduling algorithm was used to determine how many janitors to hire. We’ll measure the model’s effectiveness and make future recommendations. Infrared, temperature and humidity sensors create an IoT bathroom. Sensors have been studied to understand how to adapt them to the hygienic and private toilet environment. Sensor accuracy and cost-effectiveness could be enhanced with more development and testing. The Auto-Regressive Integrated Moving Average (ARIMA) model accurately predicts time series lags, making it a good candidate for predictive maintenance. Long Short-Term Memory (LSTM) is good in time series predictions, therefore it’s fair to compare the two. We use the ARIMA model to handle Remaining Useful Life (RUL) prediction techniques by altering Moving Average (MA) and Auto Regressive (AR). A genetic algorithm is used to create a janitorial cleaning schedule. The genetic algorithm was proposed to schedule cleaning workers. This approach improves the genetic algorithm by studying soft and hard scheduling restrictions. The Greedy algorithm is used to compare. Experimental evaluations reveal that the suggested model ARIGA meets both goals.

Agricultural production is on most countries’ national agenda because climate change affects crops, fruits, vegetables, and insect infestation. Therefore, achieving maximum production results is a challenge faced by professional growers, who have seen greenhouses as a very good option to guarantee these results. By using new technologies inside greenhouses, farmers can reduce the damaging effect of insects on plants and improve indoor cultivation through climate control. However, to efficiently manage agricultural fields and greenhouses today, farmers have to apply technologies in line with Industry 4.0, such as: robots, Internet of Things devices, machine learning applications, and so on. In this context, deploying sensors plays a key role in collecting data and finding information supporting the farmer’s decision-making. As a feasible solution for small farms, this paper presents an autonomous robot that moves through greenhouse crop paths with previously-planned routes and can collect environmental data provided by a wireless sensor network, where the farmer does not have previous information about the crop. Here, an unsupervised learning algorithm is implemented to cluster the optimal, standard, and deficient sectors of a greenhouse to determine inappropriate growth patterns in crops. Finally, a user interface is designed to help farmers plan both the route and distance to be traveled by the robot while collecting information from the sensors to observe crop conditions.

In this letter, we present a smart glove for Tactile Internet applications. The individual finger motions are measured via resistive strain sensors. The strain sensors are directly integrated with the textile glove and are produced in an automated process. The sensor glove is integrated with sensor conditioning, controller, wireless frontend, and battery. We investigate the measured sensor data for a variety of gestures, demonstrating the good quality of the data allowing for easy and low-energy gesture recognition.

There is a growing tendency for people to spend more and more hours of their day sitting. This position leads to an increase in the postural problems in the population. For workers who have to spend long hours at work, in a seated position, investment should be directed towards the development of equipment that improves their working conditions, such as smart instrumented chairs with warnings of changes in position. With this work we propose a standard office chair instrumentation approach, designed to allow monitoring physiological parameters such as: posture of the seated person (user); body temperature; and respiratory frequency. The system also allows monitoring environmental parameters such as: temperature; relative humidity; atmospheric concentration of carbon dioxide (CO2); noise; and light levels. The chair enables the interaction with control equipment to adjust the comfort level, advising the need for rest time, repositioning notifications, and the real time visualization of data, using applications for Windows and Android. The system was tested by six users and evaluated in the detection of six different postures for each user, while sitting on the chair, presenting an 100% accuracy on the posture detection and a maximum of 18% error on the physiological parameters sensing. Experimental results show the adequate functionality of the instrumented chair, which could contribute to the prevention of pathologies associated with improper posture and the improvement of work productivity

Driving behavior is an important aspect of maintaining and sustaining safe transport on the roads. It also directly affects fuel consumption, traffic flow, public health, and air pollution along with psychology and personal mental health. For advanced driver assistance systems (ADASs) and autonomous vehicles, predicting driver behavior helps to facilitate interaction between ADAS and the human driver. Consequently, driver behavior prediction has emerged as an important research topic and has been investigated largely during the past few years. Often, the investigations are based on simulators and controlled environments. Driving behavior can be inferred using control actions, visual monitoring, and inertial measurement unit (IMU) data. This study leverages the IMU data recorded using a smartphone placed inside the vehicle. The dataset contains the accelerometer and gyroscope data recorded from the real traffic environment. Extensive experiments are performed regarding the use of a different set of features, the combination of original and derived features, and binary versus multiclass classification problems; a total of six scenarios are considered. Results reveal that “timestamp” is the most important feature and using it with accelerometer and gyroscope features can lead to a 100% accuracy for driver behavior prediction. Without using the “timestamp” feature, the number of wrong predictions for “slow” and “normal” classes is high due to the feature space overlap. Although derived features can help elevate the performance of the models, the models show inferior performance to that of using the “timestamp” feature. Deep learning models tend to show poor performance than machine learning models where random forest and extreme gradient boosting machines show a 100% accuracy for multiclass classification.

Working from home (WFH) online during the covid-19 pandemic has caused increased stress level. Online workers/students have been affecting by the crisis according to new researches. Natural response of body, to external and internal stimuli is stress. Even though stress is a natural occurrence, prolonged exposure while working Online to stressors can lead to serious health problems if any action will not be applied to control it. Our research has been conducted deeply to identify the best parameters, which have connection with stress level of online workers. As a result of our research, a desktop application has been created to identify the users stress level in real time. According to the results, our overall system was able to provide outputs with more than 70% accuracy. It will give best predictions to avoid the health problems. Our main goal is to provide best solution for the online workers to have healthy lifestyles. Updates for the users will be provided according to the feedback we will have in the future from the users. Our System will be a most valuable application in the future among online workers. GSR sensor and control modes are the inputs gets from stressed human and process digitally by analysis and suggestions for stress management like mediation, yoga, music or exercise made accordingly also playing the video of the same correspondingly.

In today's world agriculture plays a very important role in the manufacturing of textiles, clothes, production of surplus number of crops that is food, which is essential for the everyday livelihood of mankind. On the other hand, there are a lot of challenges in the agricultural industries such as unpredictable natural disasters such as droughts, famines, floods etc., which can incur huge loss for the agriculture industries as well as the countries which have an agrarian society not only will it be affected by natural disasters but can also be affected by the diseases, which have the potential to destroy crops. The primary objective is to assist farmers and agriculture industries to thrive so that there can be less occurrence of food shortages by efficiently increasing the production of crops tenfold, analyzes the soil fertility for better plant growth, helps prevent plant epidemic by analyzing which fertilizer is better suitable for the protection of the plant to analyze the weather and the plants that is suitable to grow in the particular weather condition and predict the occurrence of natural disasters such as droughts and floods for early prevention from the crops by using the ATMEGA controller.

In the Existing system, the dramatically increasing deployment of the Internet of Things (IoT), remote monitoring of health data to achieve intelligent healthcare has received great attention recently. In the Proposed system, Health chain, a large-scale health data privacy preserving scheme based on block chain technology, where health data are encrypted to conduct fine grained access control. In the modification, Modification part is our implementation. We deploy the Anytime Medical Counter in all the rural areas where people cannot get good / best doctor on track. We install Heart Beat, Temperature sensor; Ultrasonic sensor, load cell, Camera and Head phone are also connected to the Medical machine. Medical counter user and is monitor from the remote area. Application is installed in both the ends for voice communication & chatting with doctor. Doctor examines the Patient and prescribes the medicines and the Medicine Dispatcher will Dispatch the Medicines from the AMM machine to the user. User can send the request to the server to get the tablets intake timings.

Over the decades, there has been a sustained effort to use fashion as a medium for delivering digital functionality. The goal is to integrate information technology (IT) into clothing to provide users with functions to assist them in their tasks. Wireless body area network (WBAN) are rapidly becoming increasingly available, accessible and importantly affordable, hence their application into healthcare to enhance the medical use of data is certain. Whether it relates to monitoring, or post-operative rehabilitation, applications are already being investigated for their role in the doctors. Wearable Technology is the addition of artificial information to one or more of the senses that allows the user to perform tasks more efficiently. we propose a system in which important information for the doctors are displayed on specific cloud for data analysis. In this project, the real time data of humans collected by the sensors attached to persons coat once the sensor measured the values then it is processed and send to cloud using IoT Medium and alert if abnormal condition occurs. The doctor can take appropriate action based on the person’s current health condition.

Digital pill is basically a multichannel sensor used for remote biomedical measurements using micro technology. This is used for the real-time measurement parameters such as temperature, pH, conductivity and dissolved oxygen. The sensors are fabricated using electron beam and photolithographic pattern integration and were controlled by an application specific integrated circuit (ASIC).This paper proposes a smart pill with remind and consumption function. Which is used to give alert the user to take pills at a particular time and the pills required to take at that time comes out to the user to avoid confusion among medicines. Smart pill box can reduce elderly family member’s responsibility towards giving the correct and timely consumption of medicines. This system Get the feedback about pills from the user and Send purchase order to medical shop.

Borders demarcate the geographic boundaries of a political territory. Borders are critical to a state’s security and carve out its physical place in the international system. When a state cannot control its borders, derive revenue from trade that flows through them, and ensure that illegal trade in commodities (and people) is minimized, the integrity of that state is undermined. Insecure borders can ultimately jeopardize stability and increase the likelihood of conflict. Post-conflict countries rarely have a robust border security system, which is especially important for preventing spoilers from destabilizing the state. Borders can either be prosperity-generating as cooperating states transfer goods, or they can be a porous membrane through which, small arms, and human trafficking pass easily. Fragile states need to protect themselves internally and engage internationally through the legitimate transfer of goods, peoples, and services, or else they are vulnerable to sliding back into conflict. Building and reforming the border security system in post-conflict states is necessary for a successful peace building process. Securing borders is a complex task that involves many different government agencies and professional skill-sets. Border guards, customs, import and export controls, and monitoring of land crossing, air and sea ports, as well as control of transactions are all critical to manage threats from illicit trafficking and facilitate legitimate movement and trade. This range of actors must coordinate to effectively manage borders and promote the states security. The bio-inspired approach to determine group size by researching and simulating primate society. Group size does matter for both primate society and digital entities. It is difficult to determine how to group mobile sensors/robots that patrol in a large area when many factors are considered such as patrol efficiency, wireless interference, coverage, inter group communications.