Since its inception more than a decade ago, Internet of Things (IoT) technology has been guiding people in the development of a world full of smart solutions in which all devices and physical objects, represented as ‘‘things,’’ are interlinked with sensors using the Internet. In some areas, the delivery of medications to patients or receivers at their destinations remains highly outdated and informal. In smart medicine delivery, the medicine needs to maintain its original state while facing multiple environmental factors, such as temperature fluctuations, humidity, etc. This paper presents an effective implementation of IoT (Internet of Things) for monitoring the transportation of medicines and vaccines, along with temperature control facilitated through mobile applications and sensor networks. The system employs mobile applications as the user interface, utilizes, MQTT (Message Queuing Telemetry Transport) for communication, incorporates a temperature sensor, and employs a mini portable cooling box. Designed for the generalized delivery of medicines/vaccines from sender to receiver, the system also suggests CRC-32 as an optimal algorithm for error detection instead of complex hash functions such as MD5 and SHA, ensuring better performance, smooth operation, and data integrity. In addition, elliptic curve-based shared keys are used for protected data transmission.

The preservation of aquatic ecosystems and the availability of drinkable water sources depends on the protection of water quality. This is especially true about bodies of water such as ponds. Traditional monitoring techniques frequently require a significant investment of resources and have a restricted application, which has prompted the investigation of more effective technologies. We present a unique wireless acquisition system for monitoring real-time water quality that makes use of the microcontroller. This system allows us to collect data in real-time. This cutting-edge technology collects data from a variety of pond locations utilizing three individual sensors to perform remote measurements of three critical parameters: turbidity, TDS, and pH. The integration of the system with an aquatic boat enables complete sampling from the center as well as the sides of the pond, which is a significant step forward in terms of innovation. The collected information, which may include pH, turbidity, and TDS readings, is uploaded to the cloud so that it may be evaluated in real-time using the AquaSpecs app. The effectiveness of the proposed system has been proven by deployment in four ponds in Chhattisgarh; these ponds are named Birkona Pond, Budha Pond, Dagania Pond, and Kushalpur Pond. This deployment demonstrates the system’s potential for effective water quality monitoring and management.

This comprehensive review explores IoT innovations in water, wastewater management, and water quality monitoring, emphasizing the transformative potential of these technologies. Combining sociometric and systematic review (SR) techniques, the study analyzes sciento metric trends and co-occurrence networks linked to review topics. Research primarily centers on these aspects, averaging 15 articles annually since 2017, peaking at 24 in 2021. The SR unveils the widespread use of multiple sensors in monitoring, particularly water level, flow, and pH sensors. Common wireless technologies are emphasized for their role in advancing real-time monitoring. Innovative protocols such as Sigfox and Zigbee enhance sensor- IoT connectivity, improving communication in infrastructure management. Common challenges hindering system efficiency and data flow include sensor accuracy, energy optimization, communication reliability, interdisciplinary collaboration, and sensor coverage. Addressing these gaps is crucial for advancing IoT driven water systems and enhancing decision-making. This study guides IoT practitioners in integrating automation and sustainability in water and wastewater management.

This paper presents a novel system for smart waste management using IoT technology. With the rapid growth of urban areas and population, proper waste management has become a crucial issue for maintaining a healthy environment. The proposed system utilizes weight sensors and ultrasonic transducers to monitor the fill levels of dust bins in real-time. The system provides a user-friendly web page that displays a visual representation of the garbage levels in each bin, allowing users to take appropriate actions based on the status. The system also sorts trash according to their weight, providing a precise idea for transportation of products. The proposed system offers an innovative and advantageous approach to waste management, promoting efficient and sustainable practices.

Advanced Internet of Things (IoT) technology has a profound impact on improving the intelligence level of intelligent transportation systems (ITS) and promoting the sustainable development of urban transportation. However, how to use IoT to process traffic flow and make ITS develop toward automation and global control is still a challenge. Against this backdrop, a prospective traffic controlling model is proposed for ITS based on IoT to enhance the awareness of roads and the responsiveness of transportation system. When traffic congestion events occur, ITS can provide the optimal control strategy of vehicle-to-everything supported vehicles (V2X-supported vehicles) from a macro perspective to control the traffic flow globally and improve traffic efficiency. Specially, the optimal control strategies consider the potential congested road segments caused by congestion propagation. Meanwhile, this article explores the impact of route choice behavior of V2X-supported vehicles on system performance. The simulation results show the optimal control strategies can alleviate congestion effectively and improve transportation system performance significantly by controlling vehicles.

This paper introduces an intelligent vehicle system implemented through Internet of Things (IoT) technology, employing various sensors for comprehensive vehicle monitoring.The microcontroller processes sensor data and manages the system's actuators. The system focuses on enhancing vehicle safety by detecting drunk driving, accidents, and driver fatigue. Recent techniques, including machine learning algorithms for improved detection accuracy and edge computing for real-time processing, are explored. Challenges faced by such systems, such as sensor calibration, data accuracy, and the integration of complex algorithms, are acknowledged. Despite these challenges, real-world evaluations confirm the system's effectiveness in identifying instances of drunk driving, accidents, and driver fatigue. The system consistently delivers real-time vehicle tracking information and antitheft alerts. The proposed intelligent vehicle system aims to address these challenges and significantly improve vehicle safety and convenience. It is designed to be innovative, cost-effective, and user-friendly, making it a valuable asset for any driver.

The term Internet of Things (loT) refers to the stage in which the internet evolved and created a global infrastructure for communication between machines and people. loT has the ability to significantly improve public safety by providing real-time data, enhanced communication and automation capabilities. This paper aims to explore the overview, characteristics, applications, public safety technologies and functional view of loT in detail. It will also discuss various applications of loT across different industries such as smart homes, smart cities, industrial loT, healthcare, and agriculture.

Forest plays a crucial role in maintaining the ecological balance of our planet. It is unfortunate that this balance is under threat due to the practice of logging, where trees are logged from forest. This destructive activity depletes forest cover and disrupts the ecosystem putting numerous species at risk of extinction. The proposed system monitors the forest by utilizing sensor and neural networks which ensures protection against logging activities. The system utilizes a combination of tilt, IR and temperature sensors strategically placed to detect anomalies in the forest. Upon the breach of predefined thresholds in sensor data, the system triggers the activation of buzzers and water pumps, providing an immediate response mechanism to mitigate potential threats. The system remains vigilant in detecting forest fires, which pose another threat to the ecosystem. This synergistic methodology entails the aggregation, processing, and notification, presenting a robust toolset for conservation initiatives.

Street lights currently use more energy than other types of lighting because of an inefficient mechanism that makes the bulbs use a lot of electricity. The suggested approach uses various sensors on intelligent streetlights to keep an eye on and manage the lights. It has sensors for measuring temperature, brightness, and power that control dimming levels and keep track of status. One Zigbee network serves as the connection point for these lights. In the modification, a cloud- and IoT-based installation was made. Through Zigbee -based data transmission, sensor values are recorded on a distant server known as the Cloud. Additionally, it lowers electricity theft. We include a trash can notice in addition to this street light idea. When the garbage can is whole, a machine automatically notifies the business as people approach the sun, and the brightness of the street lights changes or is increased.

The rapid growth in urbanization and population has increased the generation of municipal solid garbage, providing significant challenges to waste management systems. Hence, to solve the issues in waste management, it suggested Internet of Things (IoT) smart-based Smart Waste Management (SWM) with level indications. This system combines IoT technologies to improve the efficiency and sustainability of the garbage disposal process. The suggested SWM system includes sensor-equipped garbage bins that can monitor and transmit accurate information on their fill levels. Sensor-equipped garbage bins optimize waste disposal by providing real-time data, enhancing efficiency and providing timely predictions in trash management. Furthermore, the use of smart garbage bins helps the separation of various types of waste, increasing eco-friendly behaviors and helping recycling activities. The level indicators not only improve efficiency but also help to reduce environmental effects by lowering overflowing bins and eliminating waste. As a result, this research makes use of the architecture, functionality, and potential benefits of the IoT based SWM system, highlighting its role in supporting responsible waste management practices, resource conservation, and the development of urban areas.

Traditional waste management policies have historically prioritized the transportation of scattered waste to final disposal sites without prior procedures for sorting, recycling, or reuse. This approach places significant emphasis on waste reduction and enhancing waste recovery through rearing of maggots, notably maggots of BSF (Hermetia illucens). The quantity of eggs produced are contingent on environmental conditions within the breeding facility. An increase in fly egg production correlates with a greater yield of maggots and an elevated consumption of waste materials. Nevertheless, this research assumes critical importance of generating a substantial volume of BSF eggs by fortifying the resilience of the BSF breeding environment through the deployment of sensor nodes, controller-based networks and Antares. This augmentation facilitates the uninterrupted egg-laying process by flies, unaffected by their immediate surroundings. The research methodology adopted here strives to optimize the production output of BSF eggs via the implementation of an Internet of Things (IoT) system built in the controller, coupled with the utilization of the system. The temperature range produced in this study was 23.5 to 31 degrees Celsius, with humidity levels between 53.1% and 76.4%. With this temperature and humidity range, the rearing results from this research ranged from 1 gram to 4 grams, with an average of 1.8 grams

The smart metering in the smart home application is vital one to ensure the reduction of energy usage and become a hot topic in the research field with the increasing usage of energy in both industrial and residential. With the advance technologies the energy saving techniques are used for the smart homes. The Internet of Things (IoT) devices are used for monitoring, controlling, and detecting the devices for the smart home applications. In this study, a novel Deep Belief Neural Network (DBN) approach for analyzing the data that are gathered from smart home applications with IoT devices, and big data technologies which promises the smart metering in smart home applications is proposed. The energy consumption patterns and classifications are effectuated with the proposed DBN approach and ensures the safety of the home. Experimental study was made and analyzed the performance of the proposed work in terms energy consumption of different devices of smart home applications. Our proposed approach surpasses all the other approaches for the smart metering based smart applications.

Energy conservation is the prime move for reducing power production through conventional resources, which in turn leads to environmental pollution. Most of the users are unaware of their energy usage, due to which they cross their utility limit, which in turn means they need to pay a higher price. The Indian government mandates the payment of electrical energy utility bills based on slabs. Most of the users may not be aware of their utility; due to slight variations in energy consumption, they may fall into a higher slab, so they need to pay their bills more than they expected. The proposed method aims to prevent such situations by providing the user with appropriate notifications. Knowing their current utility allows them to plan their electricity bills. This system warns and informs the user frequently, at a predetermined interval. This system incorporates an IoT feature, so the user can control their utility from any place. It is an energy-efficient mechanism that drives both energy conservation and user satisfaction.

The development of radio electronics in the 21st century is associated with the automation of human activities and the monitoring and measurement of production process parameters. Using wireless communication systems facilitates the remote monitoring of parameters and provides opportunities for real time control. The efficiency of Internet of Things devices can be achieved through the rational distribution of loads, thus providing a design potential for energy-efficient smart city or smart house systems. The monitoring of power consumption is an important step toward the efficient usage of energy resources. It helps increase the operational reliability, environmental performance, and safety of electronic devices. This article discusses the usage of wireless and cloud technology for the optimization and monitoring of power consumption by smart house and smart city systems. The authors analyzed the key integration areas for the technical solution based on the Internet of Things concept. They developed a smart meter module and data processing algorithms that provide power consumption recommendations. The smart meter consists of a regular electricity meter and an extension module with a wireless connection. The data is processed with the SmartThings platform. The experimental data obtained on the laboratory setup showed the efficiency of the algorithms used and the efficiency of integrating the meter into the existing systems, as well as the economic feasibility of the solution.

Environmental concerns have garnered widespread attention, but electricity consumption continues to contribute to environmental pollution. To effectively conserve energy, users must have a clear understanding of individual appliance consumption. Existing energy feedback systems often present technical data that is inaccessible to most users. The most efficient approach to address environmental concerns associated with electricity consumption is by minimizing usage. This challenge is addressed through the creation of the Smart Energy Consumption Monitoring System. It enables users to manage power consumption within their building, providing real-time insights into electricity usage and automatically generating consumption reports. The system is designed to enhance the comfort, security, and energy efficiency of modern homes. The fundamental elements of this system consist of the microcontroller, which serves as the central hub for controlling temperature, light intensity, and motion detection. Multiple sensors, including temperature sensors, light sensors, and motion detectors, are strategically placed throughout the home to monitor and respond to environmental changes. The controller orchestrates the data from these sensors, allowing homeowners to remotely control temperature settings, adjust lighting levels, and receive real-time alerts on detected motion. This level of automation not only increases convenience but also enhances security by deterring potential intruders through intelligent lighting and motion-activated alerts. The proposed energy detection device utilizes an controller and various sensors like the ACS712, electric meter, and Wi-Fi connectivity. Collected data is analysed using the Internet of Things (IoT) technology, facilitating seamless power consumption monitoring and management from anywhere, at any time.

In today’s rapidly changing digital world, smart home automation has become increasingly popular. It has revolutionized house systems and improved comfort, efficiency, and safety, especially for the elderly. For senior citizens, keeping a home safe at each level is very important to avoid any type of hazards. In this paper, a home automation system has been developed focusing on affordability and safety. Using microcontrollers such as controller, several sensors and mobile applications, a smart home automation system has been built to ensure the safety of a home at a low cost. The Internet of Things (IoT) has also been introduced in this system which gives the power to operate electrical appliances using smart devices. The proposed home automation system redefines contemporary living standards by integrating safety assurance into daily activities and boosting comfort and security. After installing important sensors, testing, and connecting through the internet, the proposed system can ensure a secured smart home with an affordable budget for the elderly. This system has worked greatly in making a home smart and safe. The system provides its services to the user when they are at home as well as away from the home. Specially, this system ensures the safety and security of the home by sending immediate notifications and alerts to the user if any inconvenience happens in the house such as fire and gas leakage. By monitoring the presence of someone when they come in front of the door, the system also notifies the user through a message or email.

The abstract describes an extensive technique that uses gas sensing, and triad spectroscopy to detect pesticides. Triad spectroscopy sensor measures the presence of pesticides by examining light intensity at different wavelengths. Gas concentrations are simultaneously measured by gas sensors. A Python-based system that processes the gathered data using machine learning methods receives it. A buzzer sounds to inform users if pesticides are found; if not, an OLED screen shows that the sample is pesticide-free. An adaptable and efficient pesticide monitoring system is provided by this integrated 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 computzing 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.

Smart health monitoring systems, powered by and IoT, are transforming healthcare by enabling continuous, real-time patient monitoring. In India, where lapses in health monitoring contribute to 20% of premature deaths, our innovative solution addresses this urgent need. Designed specifically for elderly care, the system integrates advanced technology for health monitoring and medication management. It continuously tracks vital signs like heart rate, and temperature, sending immediate alerts to caregivers and medical professionals upon detecting abnormalities. This proactive approach not only enhances patient care and response times but also supports preventative care, ensuring timely interventions. With its comprehensive monitoring and user-friendly interface, the system is crucial for improving elderly healthcare.

The integration of real-time sensing via Internet of Things (IoT) technology has paved the way for innovative solutions to address various crucial challenges in agriculture. One such challenge is the effective management of agricultural storage facilities for reducing the spoilage and storage losses prone to happen during the storage of farm produce such as onions, potatoes, fruits like mangoes. The losses can happen due to moisture loss, sprouting, rottening, fungal/ biological infections. Some of these deteriorations are directly related to microclimate conditions inside the storage units. Thereby, preventive measures based on real-time monitoring of microclimate conditions such as temperature, humidity, CO2 build-up inside the storage can help to increase the shelf-life and reduce the losses. Further, microclimate conditions at different storage compartments are different. This paper presents a comprehensive study on the implementation of a smart agricultural storage monitoring system utilizing a Bluetooth Low Energy (BLE)-based wireless sensor network and IoT technology for recording microclimate conditions at every storage compartment (zone) in real-time, and mobile application to give remote access to real-time, zone-wise data on the mobile. This enables timely decision-making to prevent spoilage, optimize storage conditions, and efficient storage monitoring, leading to sustainable agriculture practices for storage.

Internet-of-Things (IoT) technology addresses the issues of water loss by efficiently monitoring the water levels, spotting leaks, and refill tanks when needed Notably, this technology can also supply end users and other expert's real real-time feedback through a smartphone or webpage. Review articles on smart water monitoring, including water quality, supply pipe water pipes, and recycling water waste, and freely on hand in the literature. One of the most prevalent issues worldwide is water leaks in the pipes. The local water distribution authorities typically have trouble in finding the fault's location. Numerous things, like the pipeline's aging or ongoing construction in cities, can result in leaks. This research study intends to create an Internet of Things (IoT)-based leak detection system using the Arduino IDA open source software. To measure water flow, we designed a prototype with two sensors at the destination and the origin. If leakage appears, a message will be sent to the user's mobile phone.

Theft is a crime that is growing increasingly common. Every building, be it residential, commercial, or otherwise, is insecure. Security and safety are highly valued by all people. Particularly with the current environment where crimes are increasing daily, we need to feel more secure. This paper presents the development of the theft detection using Ultrasonic sensor with the aid of Internet of Things (IoT). The main parts of this project are an controller and an ultrasonic sensor for user identification and notification. In this project, an ultrasonic sensor is used to identify the object. The user's Blynk app receives notifications via the Wi-Fi module. The primary controlling device for the project is an controller. An microcontroller is linked to an Wi-Fi module and an ultrasonic sensor. The controller is reading data from the ultrasonic sensor continually. The sensor will identify theft when it happens and communicate the processed data to the controller. The alarm will sound, and the LED will light up. The user's mobile device receives notifications from controller about Blynk warnings via Wi-Fi

This growing demand for parking spaces in urban areas has resulted in increased congestion and inefficient parking space utilization. To address these challenges, a digital parking infrastructure has been proposed. This system employs a network of sensors, cameras, and communication modules to collect real-time parking data, including occupancy status and vehicle movements. Additionally, the IoT-APS (Adaptive Parking System) provides personalized parking recommendations to drivers based on their preferences and real-time traffic conditions, enhancing the user experience.

This study presents a technology for developing an IoT- Based Drug Dispenser to enhance adherence to drugs by the elderly. With the option to automatically dispense pills and liquid medications and a user-friendly interface for caregivers, the system ensures medications are accepted on time and enables simplified compliance monitoring. The system integrates an controller that acts as a slave and controls various hardware components, The controller hosts a web application that schedules drug delivery and communication, while the controller manages all sensors and actuators involved in delivery. Use of an intuitive, web-based application enables caretakers to prescribe medications remotely, obtain notifications, and supervise drug usage. With the deployment of the described medication dispensing system based on IoT technology, an impressive increase in medication adherence is seen in elderly patients. The impact was that adherence improved notably through real-time monitoring dueto scheduling alerts and remote management features resulting in reduced missed doses. By and large, the elderly population’s problem of not taking their medicine was addressed using the IoT-enabled medication dispenser, leading to better patient results as well as quality of life improvements

Electric vehicles (EV) are getting more and more popular in today’s society as a result of rising petrol prices. An IoT-based automated breaking Control system for EV vehicles is proposed in this paper, together with a monitoring system. An EV’s battery monitoring and control system measures the battery’s voltage and temperature. Sensors, a microprocessor, a Wi-Fi module, and a battery make up this system. It is built using the affordable microcontroller. It has an ultrasonic sensor and works as an automated braking system. The controller receives the data sent by the ultrasonic sensor, which is used to identify obstacles, and uses them to regulate the brake mechanism. Voltage, temperature, and battery data are passed to the microcontroller, which subsequently sends them over Wi-Fi to the Blynk application. It is suggested that the parameters of the EV be monitored immediately using a Blynk app.

Fire accidents are the most dangerous and fatal accidents that occur as a result of worker negligence and inadequate supervision. The primary goal of this research work is put out the fire as quickly and effectively as possible. This project effectively extinguishes the fire by spraying water at that specific location, requiring less water than the traditional approach. The proposed design includes a flame sensor, a temperature sensor, and a gas sensor to determine whether a fire accident has happened. To do this, the sensors are positioned on top of a rotating platform that is connected to the servo motor. Due to this effective detection, the fire will be detected at an early stage and extinguished using the nozzle linked to the rotating base. All logical processes are performed by using controller. Furthermore, the fire activity can be monitored using IoT with the help of Blynk.

An efficient and reliable security system is always an important requirement for residential buildings. Though there are already some options available in the commercial home security segment, the budget constraint always plays a vital role for the general customers. In this paper, a customizable and scalable home security system has been developed based on controller keeping in mind the price constraint. The Internet of Things (IoT), which is an important modern technology, has also been incorporated in this system to make the system smart, reliable and fast. Controller are programmable according to the need. Smoke detector, ultrasonic sensor and LDR sensor have been incorporated for taking inputs from the real world environment. The use of IoT makes it possible for the user to access the sensor data in real time from anywhere in the world. In addition to that, an alert system has been developed, which analyzes the information and alerts the user even at a far distance in the real time.

The majority of disabled people depend on others to take care of their daily need, particularly while moving from one place to another. Wheelchair users need ongoing support to get their wheelchairs going. The people in need can use a wheelchair control system to increase their level of independence. Voice recognition technology is used by the wheelchair's control system to begin and control every movement. To operate the wheelchair, it combines a motor control interface board, a microcontroller, and voice recognition with Google Assistant. With the device, users can voice orders into Google Assistant to operate the wheelchair. The basic operational technique includes turning left and right, moving ahead and backward, and other basic working processes. and come to an end. The system encourages self-reliance, gives caretakers comfort, and lets users take an active role in their everyday lives.

This paper presents a novel moving wheelchair system, leveraging the Internet of Things (IoT), which aims to enhance the lives of wheelchair-bound individuals through obstacle detection and health monitoring. The system incorporates cutting-edge technologies, including an accelerometer for fall detection and a heart rate monitor, ensuring continuous health monitoring for the users. To address the issue of potential collisions, ultrasonic sensors are employed to detect obstacles, promptly notifying the user through an alarm. Additionally, a mobile application accompanies the system, enabling remote monitoring of vital health parameters, such as heart rate, as well as fall detection. By integrating these advancements, the proposed system aspires to significantly enhance the independence and healthcare services available to wheelchair users, ultimately leading to a better quality of life.

Many coal excavators are worried about their security in the working environment. Inside subsurface mines, unfortunate ventilation opens laborers to poisonous gases, intensity, and residue, which can prompt disorder, injury, and demise. this work proposes an idea for a Web of Things (IoT), remote sensor organization (WSN) that can follow temperature, moisture, and gas in an underground mine. This gadget utilizes a low-cost, less-power, gas sensors, DHT-11 sensor, Hub MCU, fire sensors to recognize fire and send a caution, and LDR to distinguish light contingent upon light levels. Customary coal mining tunnel noticing structures are consistently wired association systems that expect a critical part in ensuring coal mine security. With the constant augmentation of mining zones and significance in coal mines, various laneways have become outwardly weakened domains with different mystery gambles. Besides, laying links, which is exorbitant and tedious, is awkward. To resolve the issues, a coal mineshaft security checking framework in light of a remote sensor organization and the Web of Things, which can build the observing level is made. Numerous miniature sensor hubs with little measurements and lower prices make up an IoT and remote sensor organization.

Cigarette smoking is considered as a bad habit since, it is having a bad impact on health and also for the Environment. Nowadays, most of the people are using cars for their transport purposes and we already know that cars are mostly closed area, so, the environment in the car should be healthy and drivers should drive safely. Humans can be affected by Second hand smoke and Third hand smoke. This Hear Smoking is a smoking detection system in the car, which detects the smoking events inside car and notifies to the owner of the car and also stops the motion of the car. Using Internet of Things, we are going to implement this system inside the car which gives alert messages to the owner of the car, whenever the people inside the car or the driver smokes. This system can be beneficial to keep the environment in the car healthy and can be helpful for safe driving. For this, we will be using Arduino programming and mainly MQ2 and MQ135 sensor to detect smoke.

Algerian aquaculture is currently experiencing a boom in production, especially in the sub-Saharan regions (Ouargla, El Oued, Bechar, etc.). The tax advantages granted to the fishing and aquaculture activity would boost the sector, have a positive impact on prices and motivate project promoters to embark on this activity and develop their projects. however, intensive aquaculture practices have raised concerns about water quality degradation and increased susceptibility to aquatic diseases. Consequently, effective water quality management is crucial for sustainable aquaculture operations. This study introduces an innovative approach: an IoT-enabled system tailored for monitoring water quality in fish farms located in Algeria. The system's design and implementation empower farmers with real-time monitoring capabilities for vital physico-chemical parameters in nursery ponds. These parameters include turbidity, water level, temperature, pH, and more. The simulation results obtained validate the efficacy of the algorithms proposed.

Healthcare tracking systems have become increasingly important and technology focused. Due to patients not able to receive timely medical attention they undergo many problems from a variety of illness. In order to ensure that patients receive better treatment, the main objective is to establish a dependable Internet of Things (IoT) remote healthcare observing method. This would allow medical practitioners to use an IoT centered integrated healthcare structure to observe their patients, whether they are in the hospital or at home. A wireless healthcare detecting scheme that is centered on mobile devices is created. It provides real-time online data about an individual physiological conditions and is primarily composed of sensors, a data acquisition unit, controller. The method records, exhibits, and stores the individual’s temperature, ECG, heart rate, EEG data. It also transmits these information to the doctor’s mobile device via an application. Hence, an Internet of Things centered patient observing method can efficiently tracks individuals’ health and protect them from critical situation.

This paper presents the implementation of an automated system that can monitor environmental and plant parameters in a greenhouse. A series of sensors connected to a Raspberry Pico collected temperature, air humidity, and atmospheric pressure parameters. Plant monitoring is done through a high-quality Raspberry Pico and camera with a wide lens. The fusion of visible and near-infrared images calculates the Normalized Difference Vegetation Index (NDVI) to study plant health. A sliding assembly with X-axis movement allows image capture for multiple plants. The movement is done using a stepper motor controlled by the controller development board. The entire system is remotely controllable via the IoT Greenhouse web application. Access to the application is conditioned by authentication, thus protecting the collected data.

There have been several attempts to use the new technology in various fields to improve the quality of life as a result of technological advancement and the shrinking of sensors. Since the last ten years, the healthcare monitoring system has evolved into one of the most important systems and has become more technologically focused. Unexpected deaths from a variety of ailments are an issue that affects people, and it is caused by a lack of timely medical attention for patients. The main objective is to create an IoT-based patient surveillance system that would assist healthcare providers in keeping track of their patients. An IoT-based integrated healthcare system can monitor this both in hospitals and at patients' homes to provide improved patient care. Medical professionals or caregivers can remotely access patient data to monitor health improvements from locations outside the hospital. The application of Internet of Things (IoT) principles has been widespread in connecting available medical resources, offering patients intelligent, reliable, and efficient healthcare. This project has introduced a specially designed IoT architecture tailored for healthcare applications. Therefore, the suggested design gathers the sensor data using an microcontroller and transmits it to the cloud where it is processed and examined before being displayed. In the event of an emergency, patients' actions based on the health data analysis can be sent back to the doctor or nurses via messaging.

The main objective of this work is to alert the farmer when an animal enters into their farm field and prevent the animal entering into the form field. The animals suddenly entering to the field is the major issue that farm owners frequently deal with. The traditional farming techniques need to be replaced with smart farming methods in order to prevent the entry of animals. The proposed system uses the sensors, controller and Internet of Things (IoT). This developed system also enables the farm owner to get the Short Message Service (SMS) through Global System for Mobile (GSM). In addition, it provides the access to the farm owner to control the entry of the animal to farm field automatically or manually from the home. As the developed system transmits the real time pictures of the animal to the farm owner through telegram bot, he/she will be well prepared to protect the animals. Further, the developed system makes use of speaker to play the same detected animal sound as a way to repel the animal. It also produces the fog and lights to prevent the immediate entry of animals. Thus, this work facilitates the smart way to control the wild animals entering to the farmland.

It is necessary to use sufficient lighting and HVAC system along with the protection to each building or houses. Proper lighting system is achieved by connecting the field devices or lights with controller and smart sensors. The controller is used to turn the lighting loads ON and OFF when the sensor input comes. Security of the building or house is achieved by installing an autonomous rover system with OV7670 Camera module. An autonomous rover is allowed to roam inside the house in all the room as per the pre taught or stored GPS positions. The motion of the rover is adjusted based on the obstacles, which are present in the motion path. The smoke sensor and OV7670 Camera module are installed in the top of the rove which is used to detect the fire and unauthorized entry of the person. OV7670 captured pictures are converted into pixels by Mean Square Error techniques. The sensor data are collected in the controller and the same is transmitted to the owner’s smart phone via Wi-Fi Module. MQ2 smoke sensors are mounted over the rover for sensing the smoke and hazardous gas leakages. The buzzer or alarm will be activated when there is any security threatening inside the building by the controller.

IOT is a technology that uses internet medium for communicating within electronic devices. It also uses sensors, actuators in order to enhance the usage. The movable dustbin developed in this paper is an Iot based model. The existing systems of movable dustbins majorly focusses on movement of dustbin based on user commands which may not be suitable for deaf-mute people. The proposed system focusses on moving the dustbin based on the user's button commands and displaying level of trash filled in user developed interface of IOT app. The lid opens when trash detected and closes after a specified time. In this paper, microcontroller has been used which is better than controller board. This model will be useful for elderly and physically challenged people

This work focuses on creating a holistic solution that integrates Internet of Things (IoT) technology with real-time monitoring to improve solar panel performance and longevity. Real-time monitoring of critical solar panel characteristics, early defect identification, predictive maintenance, and energy management are the main goals. IoT -enabled solar panel maintenance solutions can help cut maintenance costs, improve efficiency, and decrease downtime. IoT devices can identify problems before they become serious by giving insights into the functioning of the system. This allows the maintenance staff to take corrective action before any major damage occurs and therefore extends the lifespan and overall efficiency of solar power systems while decreasing maintenance costs and downtime.

Saving energy is the foremost concern in this present scenario of the modern world. The conventional method of manual or timer- controlled switching for public lighting often results in energy wastage, as lights remain on even during the day due to various reason like negligence of the lineman and without having the proper power consumption record and manual fault detection leads to addition in the maintenance cost and increases the downtime of the faulty lights. Also, at times streetlights are not powered on even though there is a lack of ambient light conditions. This leads to safety concerns for the citizens and residents of a particular place. So, to tackle these problems there was a need to build a system based on IoT that can dynamically adjust illumination based on real-time conditions, and also provide a record of energy consumption and location of faulty lights as well as predict the faults. This leads to lower operating costs and quicker identification of defective locations, reducing downtime.

This research paper presents a system model on the design and implementation of a Fire Alert System integrated with IoT for early fire detection and action. The primary objective of this work is to enhance fire safety measures by leveraging IoT technology to detect fires at their early stages, allowing prompt action to minimize property damage and save lives and rescue operations. The proposed system incorporates multiple sensors strategically placed in the smart home environment to monitor temperature, smoke, and CO levels continuously. The implemented model includes range of sensors along with OLed visual indicator and a loud buzzer to alert occupants about the potential fire hazards. Additionally, the system initiates an automatic water sprinkler system to suppress the fire in its preliminary stages. The integration of IoT technology enables real-time monitoring and remote accessibility of the Fire Alarm System. The collected data from the sensors can be transmitted to a centralized monitoring station or accessed via a mobile application, facilitating remote monitoring, analysis, and control of the fire hazards. The effectiveness of the Fire Alert System is evaluated through hardware implementation and extensive testing scenarios to assess its accuracy, responsiveness, and reliability. The research findings demonstrate the potential of IoT-enabled Fire Alert System in improving fire safety measures. The prediction of the developed system, combined with prompt alert mechanisms and automated response contributes to enhanced fire prevention for smart home and offices

The main reason for the increasing popularity of fish as pets in households is the recent scientific understanding that watching the motion of fish can create a calming environment, resulting in a stress-reducing effect on people. It has been found to lower blood pressure and promote relaxation. However, a significant issue in fish maintenance has emerged due to irregular care, leading to a rise in fish mortality rates. The primary challenges in maintaining fish aquariums are inconsistent feeding and inadequate monitoring of water quality. With busy schedules and owners frequently away from home, maintaining the aquarium becomes challenging. To address this problem, the proposed solution offers facilities that include automated feeding at regular intervals, as well as continuous monitoring of parameters such as Total Dissolved Solids (TDS) and temperature levels. Users will receive alerts when these parameters deviate from ideal conditions. By implementing these solutions, we can reduce fish mortality rates and simplify the maintenance process.

In this study, we propose to use WiFi board to measure water level in an inventive way that combines creativity and state-of-the-art technology. We further propose simple connectivity and real-time data transfer using WiFi board, allowing customers to check the water level from any position on the planet. This system also incorporates an actuator module that automatically regulates the motor according level of water. Thus, the pump will automatically shut down by minimizing energy waste and preventing waste when there is sufficient water. The method monitors and regulate the water tank without being physical presence by using WiFi board. Utilizing a smartphone or tablet, users may easily get water level data and oversight choices thanks to the implementation of the Blynk IoT app. Additionally, the precision and dependability of the readings of the water level are improved by the use of ultrasonic technology. In the end, the proposed system proposes to revolutionize the monitoring of water levels by combining state-of-the-art technology, wireless communication, and intelligent control. It proposes an effective and easy to use solution for optimal water management by supplying customers with immediate time information and automatic pump control. When compared to recent state-of-the-art systems, our system shows efficient and appropriate performance with less computational cost.

Over the past decades, agricultural production has been severely impacted by climate change, water shortages, global warming and population growth. The implementation of innovative technologies has emerged as a promising approach to address these challenges and improve the farming industry. The current study proposes an intelligent solution to the existing agricultural problems by utilizing Internet of Things (IoT) concept for environmental monitoring and irrigation facilities. The system enables the monitoring of temperature, humidity and soil moisture on-site and remotely via a device such as laptop, tablet or mobile phone trough an application. The smart irrigation system has been designed to ensure efficient water supply. It allows direct control of the water pump to prevent over irrigation. The Telegram application is employed for IoT communication and real-time data monitoring. The paper presents and analyzes results from a small-scale implementation. The prototype model has been tested on three types of soil and values were adequately recorded. Based on the research findings, it is anticipated that the based smart irrigation systems developed in this paper will contribute in the field of electrical engineering in the creation of an economically feasible solution for sustainable farming technology.

Particularly in the wake of the pandemic, tele health has gained a significant role in the delivery of healthcare globally. The use of healthcare monitoring systems has greatly increased. The goal of this project is to create a prototype home health monitoring system that can take the place of standard physical examinations performed in hospitals. The goal is to extract important health metrics from the PPG data utilising the MAX30102 Photo plethysmography (PPG) module, infrared temperature sensor (DS18B20), an OLED display, and the Blynk cloud platform. These parameters include heart rate and oxygen saturation.

This project introduces a comprehensive home automation system leveraging Wi-Fi connectivity and ESP32 micro controllers, aimed at enhancing modern living through seamless automation and user-centric design. The background emphasizes the fusion of IoT technology with home automation, highlighting Wi-Fi's significance in enabling remote monitoring and control of household devices. Methodologically, the project integrates relay modules and DHT11 sensors, orchestrated through a user-friendly smartphone application. Results demonstrate successful implementation and testing, showcasing functionality, reliability, and user-friendliness. Real-time environmental monitoring and remote appliance control fulfill the objectives of enhancing home comfort, convenience, and energy efficiency. The conclusion underscores the project's contribution to advancing smart home technologies, offering users a scalable and customizable solution. Future research opportunities include enhancing system capabilities and addressing security and privacy concerns.

This abstract outline the development of an autonomous landmine detection system that integrates the microcontroller, CAN communication, and WiFi control. The system aims to enhance the safety and efficiency of landmine removal operations by enabling remote-controlled investigation. The microcontroller serves as the central processing unit, facilitating seamless communication among system components. CAN communication protocols enable real-time data exchange between the microcontroller and the mine detector, while WiFi control allows operators to remotely monitor and control rover movements. Through comparative analysis with existing systems, the novelty of this approach is underscored, particularly in achieving higher accuracy rates and ensuring operator safety. Rigorous testing validates the system’s performance, demonstrating superior accuracy in landmine detection compared to conventional methods. This innovative system represents a significant advancement in landmine detection technology, promising to revolutionize clearance efforts and contribute to safer environments in conflict-affected regions globally.

The water purification system presented in this project harnesses the capabilities of a Raspberry Pico and an array of sensors to monitor and enhance the quality of water. It commences when an ultrasonic sensor detects the water level in the sewage tank, triggering a multi-stage purification process. The system undergoes three crucial phases: screening to remove solid particles, carbonation to eliminate unwanted chemicals and organic compounds, and RO salt pump purification to retain essential salts. The ultrasonic sensor halts the purification process once the purified water tank reaches a specific level to prevent overflow. Post-purification, a suite of sensors measures parameters like pH, gas content, turbidity, and temperature, with data transmitted to the cloud and accessible via the Blynk application. This purified water can be employed for household purposes. Future iterations may include automatic tank cleaning and maintenance alerts, adding further sophistication to this intelligent water purification solution.

Now-a-days traffic violations are increased which causes road accidents. The increase in traffic rule violation increases the accidents. In order to reduce traffic violations and road accidents, we are using traffic violation detection systems. In this paper, we propose a system to monitor the vehicle movement and track the vehicle involved in traffic violations such as signal violation, speeding and accidents. The proposed system enhances the traffic rules by detecting signal violation and alerting the vehicle owner about it and detection of speed and if the limit is exceeded then an automatic message about the details of the vehicle will be sent to the nearby control room in order to prevent hit and run accidents. The main motive behind this project is that it combines both RFID and IOT technology in order to check both traffic signal violations and the speed limit exceeding violation so that we can prevent major collisions and accidents happening in both well populated and remote areas. It also includes a webpage to control and keep records of violations which makes it easier for Traffic police to track and maintain records in order to regulate traffic accordingly in accident prone areas.

Climate change, a lack of soil nutrients, a decrease in pollinators, plant diseases, and water waste from conventional irrigation techniques that cause water clogging on top soil are all contributing factors to our nation’s food issue. The issues are resolved by the suggested model, which contributes to a rise in agricultural irrigation efficiency. Microcontroller VEGA AS1061 is used in this system. The purpose of the spack fun soil moisture sensor is to periodically measure the soil’s moisture content and nutrients in order to develop a workable and reasonably priced model. DHT11 is used to measure temperature and humidity. And PH of soil is measured by PH sensor. With the help of sim 900 GSM module the status of soil moisture, PH level, soil nutrients and temperature is sent to the farmers’ phone. Farmers are provided with information using machine learning object recognition and picture classification, which may identify pests, animals, and birds.

IoT plays a major role in the automation of various industries and has become very important for making humans life to comfort zone. In poultry farms, the IoT is used for turning on and off the lights based on the intensity of the light and the fans based on the temperature in that environment. The water supply is very important for the proper growth of the chicks or hens. So, for the continuous supply of water, the nipple line system has been introduced to the poultry farm. Since the pressure of the water is reduced before going into the nipple line to avoid unnecessary wastage of the water like overflowing of the water or leakage of the water in the nipple, this allows the hens to drink water with great comfort. But this has the disadvantage of improper flow of water or flow of water with low pressure, which could cause the air to lock or block the flow of water. Improper monitoring of the water reduces the growth of the hens. To avoid this situation, poultry farm owners use labour to continuously monitor the water, but it is not efficient. The proposed research work sense the presence of water in the nipple line, and it could send the message to the farmer's phone with the help of the GSM module. For this process, the threshold distance is fixed; if the distance is greater than the threshold distance, it could send a message to the mobile number to which it linked. By this method, the water is monitored properly, the growth of the hen is increased and the cost of labour is also reduced. It is one of the cheapest and best methods to monitor the water in the nipple line.

This study focuses on enhancing industrial safety through an advanced Industrial Safety System utilizing Internet of Things (IoT) technology., particularly in high-risk indus-tries like petroleum., chemicals., and oil. The system employs various sensors for flame., gas., and environmental monitoring to swiftly detect hazards in real time. At its core is the controller acting as the central processing unit to monitor parameters like temperature, humidity., and light intensity continuously. GSM technology enables rapid communication for prompt alerts to authorized personnel during emergencies. IoT integration facilitates seamless data exchange and remote device control., streamlining efforts and providing swift access to physical devices for a safer industrial environment. The solution aligns with Mechanical Engineering principles., offering a comprehen-sive approach to mitigating accidents caused by factors such as fire., gas leakage., and high temperature. By combining virtual monitoring with risk management., the system allows real-time access to crucial parameters., efficient analysis., identification of breaches., and timely warnings to prevent accidents. This research contributes significantly to industrial safety discourse., emphasizing technology's pivotal role in establishing secure ecosystems. IoT integration enhances monitoring capabilities., enabling a proactive and responsive approach to safeguarding industrial processes and personnel.

The rapid advancements in technology have led to the integration of Internet of Things devices to create smart and connected solutions for everyday tasks in various domains. This paper introduces a paradigm shift in the realm of grass cutter maintenance by proposing a transition from traditional grass cutters to an innovative Bluetooth-Controlled Green Sward cutter system. The conventional grass cutting approaches involves manual operation, requiring physical presence and effort. However, this method is associated with limitations such as inefficiency, noise pollution and environmental concerns. In response to these challenges, the proposed Bluetooth-Controlled Green Sward cutter system aims to revolutionize lawn care practices through remote accessibility and smart technology integration. This paper presents the development of a novel IoT-enabled movable grass cutter system that incorporates real-time camera access and remote-control capabilities through a smartphone application. This Bluetooth controlled Green Sward cutter system enhances the convenience and efficiency of grass cutter maintenance processes and help the farmers in Agriculture. The system comprises a grass cutter equipped with IoT modules including controller board as the main controller of the system, an CAM module for real-time monitoring, a HC-05 module for wireless connection, linear and adjustable blades for cutting the grass and motor drivers for the wheels of the Robot as well as for blades. The camera module allows users to monitor the cutting progress remotely and ensure precise operation. The integration of IoT, camera access, and smartphone remote control enhances the efficiency, convenience and user experience of grass cutter maintenance.

Using Internet of Things (IoT) technology in poultry and fish farming makes it possible to monitor farm conditions in real-time, send notifications to Smartphone, anticipate possible problems ahead of time, and provide prompt advice which look after the welfare of the birds, lower cost and improve output and quality. Monitoring the weather, particularly temperature, humidity and pH level of water in fish tank is an essential part of this application since these factors have a big impact on raw materials, food quality, chicken health, feeding schedules, and general farm management. An Internet of Things (IoT) - based weather monitoring system specifically designed for poultry farming and fish farming is proposed in this article to enhance productivity and optimize farm operations. A DHT11 sensor is used by the system to measure humidity and temperature. The collected data is transferred to the cloud, where it is stored in a database and regularly checked against pre-established cutoff points. The device causes alarm messages to be delivered to Smartphone for immediate attention when the data surpasses these levels for a predetermined amount of time. The suggested solution has been validated and proven to work by sending timely warnings to Smartphone when crucial thresholds are exceeded and maintains a healthy environment for poultry and fish farming.

Over the past few decades, agricultural systems have encountered significant global challenges, including short-age of food supply, declining water availability, rising input costs, and diminishing agricultural labor. The advancement of Agricultural Technology (AgTech) in recent years has increased farm productivity and replaced manual monotonous tasks that are unsafe or inefficient for farm labor workers to do by hand. In this paper, we propose to develop and implement a smart agricultural robot named SARDOG that is based on the Farm-ng Amiga robot framework. LiDAR, Internet-of-Things (IoT) sensors, and a robotic arm all of which work hand in hand to perform multiple intelligent farming tasks autonomously and effectively. SARDOG is capable of autonomous GPS-less navigation using LiDAR, picking fruits using the robotic arm, testing the soil properties using a robotic actuator sensor framework, it can follow the farmers in the field and carry the produce for them among many other applications. The purpose of SARDOG is to make multiple major farming processes more efficient, cost-effective, and humane, as well as to perform some new farming processes that are not widely explored.

This review paper examines the integration and impact of the Internet of Things (IoT) in smart grid technology, focusing on key implementations across the energy sector. These include advanced metering infrastructure, power transmission and distribution monitoring, and energy theft detection. The paper emphasizes the role of the Ubiquitous Power Internet of Things (UPIoT) in improving grid observability and controllability, and discusses advancements in machine-to-machine communication architectures that optimize metering infrastructure. Additionally, it explores the use of long-range wireless protocols for efficient data transmission within power distribution networks. The challenges and potential solutions for integrating IoT with smart home and building systems are also addressed, highlighting the innovative ’last-meter’ concept for customer-centric smart grid applications. Through case studies and experimental results, the paper provides detailed insights into how IoT technologies can revolutionize smart grid systems, enhancing their efficiency, reliability, and sustainability.

In the present era, public bus transportation services often lag behind in adopting modern technologies, resulting in numerous operational complexities. These issues encompass challenges such as poor passenger density control, operational inefficiencies, inadequate live tracking, limited real-time capabilities, suboptimal resource management, route ambiguities, safety concerns, and more. This research paper introduces a comprehensive solution an Advance Public Bus Transport Management System (APBTMS) that aims to address these challenges for the benefit of both passengers and transport management authority. Our proposed system leverages various sensors and IoT (Internet of Things) modules deployed within buses to monitor various onboard activities and physical environmental factors. These enable the making of data-driven decisions in real-time, Facilitating improved operational control. Key components of the system include GPS (Global Positioning System) tracking for real-time bus location updates, passenger density/count through CV (Computer Vision), and continuous monitoring of physical environmental factors such as temperature, humidity, sound magnitude, and vibration magnitude which facilitate accident/abnormalities detection, Fire detection and helps in continuously monitoring road quality. The application of CV technology, along with passenger count, can detect harm-causing objects inside a bus and can compare the faces of passengers with black-listed passengers (involved in previously reported crimes such as theft, and nuisance). Passengers benefit from these advancements through a dedicated mobile application. A User-friendly website is also offered to public bus transport management authority providing various useful functionalities. With the addition of safety features like real-time speed detection and many other capabilities in the future, our proposed system can expand its benefits to school bus services and other public transportation services.

The use of solar energy has increased significantly over the world. They are well-liked due to their endlessness and purity. It also stands out for being low maintenance. Yet, if a little issue with the panel or circuit is not identified promptly, it could cost a lot to maintain. Another challenging task is finding the flaw inside the vast solar field. This study examines the viability of employing IoT for real-time fault detection. Reducing the maintenance expense and detection time, Panel temperature, light intensity, and current are monitored and maintained continuously, respectively, using temperature, light, and current sensors. In the proposed study to maintain the standard level of voltage, battery voltage is constantly monitored to meet the industrial need and to increase the life span. The study also aims to measure efficiency concerning the increase and decrease in power levels. Further, the study involves a cleaning system that can be integrated into the solar panel to clean the dust layer accumulated on the panel. Cleaning dust is an important factor in solar panel maintenance to improve efficiency and reduce corrosion. The novelty of the system lies in the comprehensive approach towards solar panel maintenance through the integration of IoT technology, smart cleaning systems, and rigorous analysis of efficiency factors.

The Sun is a powerful energy source. Solar energy is a radiation from the Sun. The radiation from the Sun is capable to generate electricity. The solar energy falls on the Earth is excess then the requirement of world’s current requirement. If properly harnessed it will satisfy all our future needs. It is attractive renewable energy source due to its inexhaustible supply, freeness & non-polluting. Although it is free but it is costly to collect, convert & storage. It creates limitations to use An Internet of Things-based solar power monitoring system continually detects important factors including light intensity, voltage, current, and temperature of the solar panels. This allows us to detect & address issues promptly, ultimately improving the efficiency.

One of the numerous cloud-based services is the e-health system, which stores and shares patient medical data among healthcare professionals and patients. It operates mostly through computer or electronic systems and cloud technologies. The semi-trusted third-party supplier (the cloud) stores medical information. Consequently, security has emerged as the primary worry because no unauthorized individual ought to be able to obtain the data. To help to advance the field of e-health system security, this paper purposes to give a brief overview of the security features of cloud founded e-health systems. A study of the research on safe cloud-based healthcare systems using several techniques, including Extended Semi-shadow Images (ESSI), Medical Cloud Multi-Agent Systems (MCMAS), Adaptive Deep Convolutional Neural Networks (ADCNN), Structural Health Monitoring (SHM), etc., is presented in this paper. Additionally, certain security rules pertaining to health are discussed along with security techniques, their benefits and their drawbacks for each category. This study provides guidance for conducting additional research in the field of e-health system research because it analyses security legislation, security mechanisms, and their benefits and drawbacks

This paper introduces a system for monitoring plants using IoT technology. It combines traditional farming practices with modern sensors like those for soil moisture, temperature, and motion detection. The system, called Smart Plant Monitoring System, runs on controller and allows real-time data collection, remote monitoring, and automated irrigation. The Smart Plant Monitoring System enhances sustainability in precision agriculture by efficient use of resources such as water, fertilizers, and energy in agricultural practices, and minimizing wastage through real-time monitoring and automated irrigation. The results show significant enhancements in data collection, processing, and decision-making. The system facilitates real-time monitoring of plant health, enhances irrigation efficiency, and offers user-friendly interfaces for farmers. Key inferences include the ability to optimize irrigation, minimize resource wastage, and enable timely interventions for satisfactory plant care. Although occasional sensor inconsistencies occur, the system demonstrates overall satisfactory performance. However, refinement is needed to address sensor delays and sensitivity settings.

This article presents a safety monitoring system for coal mines using the Internet of Things (IoT). The proposed system comprises of an underground section and a ground section. Controller is responsible for monitoring underground conditions through various sensors, such as a methane gas sensor, an IR flame sensor, a Carbon monoxide (CO) sensor, and a temperature and humidity sensor. Then this collected data is sent by controller to the ground section via a wireless connection. Controller is responsible for sending alert messages through Telegram based on the readings of these sensors. The ground section, which can be a mobile device or PC, monitors the information from the underground section via a web page made using HTML, CSS, and JavaScript in real-time, with its server being controller. Additionally, controller and RFID are incorporated into the underground system to bolster safety measures. The hardware and software for the system is designed and developed in view of the conditions in coal mines. Results are presented for safe and unsafe conditions based on the predefined threshold values of individual sensors. Threshold values are predetermined based on the actual values collected from a coal mine environment. Results indicate the proficiency of the system in detecting unsafe conditions promptly and alerting both officials and workers, facilitating swift responses. By seamlessly integrating wireless technology with an advanced alerting system, the proposed solution emerges as a smart and efficient tool to enhance safety in coal mines.

This study presents a novel technique for identifying individuals using feature extraction methods and signal processing approaches. It uses an artificial neural network (ANN) technique to identify scent patterns in individuals using ten metal oxide semiconductor sensors. Sensor data is scanned and extracted before using ANN patterns. Before using ANN patterns to generate patterns from sensor data, it is important to scan and extract sensory information from that data. Each participant is recognized and scanned for a totally of 1000 different characteristics during the course of the multiple investigations, which are conducted across a variety of time periods that include 5, 10, 15, and 20 people. Because of the varying time periods, signals from sensors are received in analog form, which is then transformed by Arduino into digital form. It is necessary to train an architecture on the data set that has been created. The benchmarks that are employed for the assessment of the model that is presented for the identification of human odor include sensitivity, f-measures, accuracy, and specificity, among other things. Experiments are carried out using the assessment measures, and the findings demonstrate that this model has an accuracy of greater than 85 % in most cases. The research demonstrates the potential of feature extraction methods in identifying individuals and enhancing human odor identification.

Monitoring water flow helps to identify leaks and wastage, leading to better management of water resources and conservation of this precious resource. To address this challenge, there is a need for an efficient and sustainable water management system. This paper presents an Internet of Things (IoT) based solution that involves retrofitting existing analog water meters using readily available off-the-shelf electronic components. Real-time data collection and analysis are performed through edge computation, which locally processes water meter images captured by the camera and extracts water meter readings. These readings are transmitted to the cloud for storage and further analysis. Various strategies have been implemented to optimize supply-current usage, preserving charge-discharge cycles of solar-powered batteries even in adverse environmental conditions. To streamline the firmware update process for multiple connected devices, a broadcasting technique is employed, offering the benefits of reduced manual labor and time savings. To assess the reliability and performance of developed solution, field deployment is conducted over several months, enabling the characterization of water usage patterns across different locations. Integrating energy harvesting capabilities into system reduces maintenance costs and promotes eco-friendly energy practices. Overall, this solution offers an effective and comprehensive approach towards achieving efficient and sustainable water management.

People are preoccupied with their own duties in today’s environment, making it tough to oversee and care for disabled people. Paralyzed and disabled people, on the other hand, have a powerful desire to move around freely. Different initiatives have been taken in the past to improve and preserve the self-esteem of such people, and various technologies have also been created to assist them in a better way. The primary advantage of a vision-based autonomous wheelchair is that it can provide greater independence to users with limited mobility. The methodology of other smart wheelchairs varies depending on the specific technology used. Some smart wheelchairs may use sensors to detect obstacles and provide feedback to the user, while others may incorporate GPS and other navigation technologies to assist with indoor and outdoor navigation. Our study proposes a revolutionary implementation of an autonomous system for fully handicapped people, allowing them to drive wheelchairs using just their Self.

We constructed a smart classroom based on IoT technology, which improved the efficiency of classroom management and teaching. The status of the application of IoT technology in education was analyzed for the necessity and advantages of the smart classroom. The key technologies and core functions of the smart classroom were defined for intelligent devices, data collection and analysis, teaching aids and so on. The implementation effect of the smart classroom was evaluated and the future development direction is proposed.

A web server is being developed for embedded systems. The developed web server will display dynamically changing data. Web servers for embedded systems allow the dynamic display of data in real time via the Internet. These systems are perfect for managing physical processes, monitoring and controlling equipment, building automation, and more. Embedded web servers are compact, energy-efficient, and can operate in a variety of environmental conditions. The aim of this project is to create software code that can display real-time data from an electronic control unit using a web interface. During the development process, an analytical review of technical standards and modern technologies for displaying dynamically changing data using a web interface was conducted, and the necessary tools for development were selected. Based on written above, software code was developed to display real-time data from the electronic control unit using a web interface. This development can be used as part of a digital twin of a physical electronic device.

Innovative safety in the workplace is vital as the high safety risks associated with electrical engineering construction can lead to injuries or even fatalities. Using computer vision technology, we experimented with scenarios such as “normal operations” and “unexpected incidents” to enhance safety measures. We integrated an Internet of Things system into the setup, enabling the system to quickly detect and alert to unexpected events in real-time, thereby improving workplace safety.

Proper waste segregation is a common problem all over the world. In the past few years, the growing population resulted in the increase of waste in the environment. In this study, the Internet of Things was utilized to develop a vision-based garbage bin using multiple sensors and relay information to the system to classify waste automatically. The suggested method provided a practical solution for efficient waste classification. The classifications of metal, paper, plastic, and food waste showed precisions of 97.25, 96.75, 97.25, and 95.6%. The precision was 94.87% for the scores based on the confusion matrix. A total of 10 trials were performed for each waste and the actual and predicted results were compared. The findings showed that the combination of four garbage bins resulted in an accuracy of 91.30% in waste classification. A mobile application is incorporated to monitor the capacity of the bin. The developed integrated vision-based disposal system addresses waste-related problems specifically proper waste classification.

The rise of the Internet of Things (IoT) has sparked innovation across various sectors, with ongoing exploration and implementations aimed at tackling modern-day obstacles. Among these, transportation stands out due to the increasing demand driven by population growth. As urban areas experience a surge in vehicle ownership, the availability of parking spaces becomes a pressing issue, especially in public areas like shopping malls, parks, and theaters. While manual parking systems persist in many places, the lack of clear regulations for outdoor parking worsens the problem. Traditional methods are outdated and contribute to traffic congestion, minor accidents, and inefficiencies. To address these challenges, this paper proposes a smart outdoor parking system leveraging IoT technology, specifically utilizing embedded controllers and infrared (IR) sensors. Entry and exit gate management is also implemented to allow only users who had reserved the parking slot. An Android application is developed using android studio for users to check slot availability, reserve parking spaces, and efficiently navigate to their destinations. This system is tested on a prototype of parking area creating six parking slots. By integrating hardware, cloud, and mobile application, this system aims to transform parking management, providing structured, adaptable, and user-friendly solutions for urban parking dilemmas.