In this study, we developed a wearable eye tracker leveraging mini-infrared point sensors. The eye tracker utilized two inexpensive mini-infrared ray (IR) point sensors to measure the left-right eye movements of both eyes. These left-right eye movements, play a crucial role in monitoring and treating mental disorders such as post-traumatic stress disorder, and are essential in eye movement desensitization and reprocessing therapy (EMDR). The proposed eye tracker can track a user’s eye movements by detecting the left-right pupils. We developed a dual sensor-positioning algorithm that measures the left-right movements of both eyes using only two sensors. The strategy of positioning the sensor symmetrically between or outside the eyes allows for the precise measurement of the movements of both eyes. To validate the proposed wearable eye tracker, we analyzed the left and right eye movements of 10 participants and found that there was no statistically significant difference. Further analysis demonstrated a high correlation between the measured eye-movement and the input eye-movement. The proposed device showed the feasibility of employing a wearable and inexpensive eye tracker with only two mini-IR point sensors to accurately measure the left-right movements of both eyes.

This paper introduces a novel mathematical approach to significantly enhance dual-axis solar trackers’ Solar Reliability Factor (SRF) by developing and implementing an advanced Online Built-In Self- Test (OBIST) architecture. This innovative architecture is designed to efficiently address and correct single bit-flip errors within the system’s microcontroller unit (MCU), a common control unit in contemporary solar trackers. By employing an improved diagnostic scheme based on extended Hamming codes, our OBIST architecture identifies and autonomously corrects all detected single bit-flip errors, reducing the fault coverage. This capability marks a significant advancement in the field, directly contributing to a substantial increase in the SRF. The study meticulously analyzes the potential fault domain influenced by environmental factors such as prolonged sunlight exposure and varying weather conditions, which are critical in the regular operation of solar trackers. Furthermore, we introduce a probabilistic model for defining and addressing stuck-at-faults, enhancing the system’s overall reliability. The successful application of novel fault coverage-aware metrics demonstrates the OBIST architecture’s effectiveness in improving solar tracker reliability, significantly contributing to the photovoltaic (PV) systems domain. This research presents a groundbreaking approach to enhancing solar tracker reliability and sets the stage for future advancements in the maintenance and efficiency of renewable energy systems.

Effective waste management and pollution control are paramount for sustainable environmental stewardship. This study presents a comprehensive approach leveraging cutting-edge technologies such as YOLO object recognition, Faster R-CNN, and SVM-based AQI computation. The system integrates YOLOv7 for real-time rubbish classification, facilitating swift and precise trash sorting and disposal decisions. Additionally, it employs Faster R-CNN for fog density analysis, enabling thorough estimations of air pollution levels. To calculate the Air Quality Index (AQI), support vector machine (SVM) algorithms combine various air quality indicators, ensuring thorough and accurate assessments. Enhanced trash classification capabilities enable more accurate evaluation of the environmental impacts of waste management systems. By integrating fog density monitoring with AQI calculation, the approach offers comprehensive trend analysis of pollution, aiding in the formulation of data-driven environmental policies and effective pollution management measures. Furthermore, the system evaluates soil quality, complementing its waste management and pollution control functions. Despite its advancements, the system faces challenges in real-world implementation, including data acquisition, model training, and system integration. Addressing these challenges is critical for realizing the full potential of integrated waste management and pollution control systems.

As smart home technology becomes more and more common, there is an increasing demand for user identification techniques that are both secure and energy-efficient. This study highlights the energy economy while introducing a novel automatic fingerprint security system for smart home applications. To increase security, the suggested solution uses a fingerprint scanner. Users may control various appliances and gadgets via a website or mobile app. By activating smart appliances based on user identification, the system actively helps energy saving and offers sophisticated security features, such as room-specific access and emphasizing user-centricity. The project includes both software and hardware elements, including a database, Raspberry Pi microcontroller, fingerprint reader.

Physically challenged people have discomfort in mobility due to several illness and issues. Improvisation in the lifestyle and quality of life for such individuals is the need of the society. The proposed study focuses on the mobility aid for the physically challenged individual by integrating an accelerometer sensor and an based controller allowing for the translation of natural hand gestures into precise motor commands in order to overrule the limitations of the traditional interfacing techniques fostering independence and social inclusivity for the estimated 75 million wheelchair users globally. The accelerometer sensor plays a pivotal role in tracking and interpreting the user's hand movements, creating a seamless interaction between human gestures and the motorized propulsion system of the wheelchair. The controller serves as the bridge, processing these gestures and orchestrating the corresponding movements, namely forward, backward, right, left and stop condition. A notable feature enhancing the wheelchair's usability is the incorporation of an infrared (IR)--based remote control system. This introduces a layer of home automation, enabling interaction with the surrounding environment using the same intuitive remote-control device. The gesture-controlled wheelchair seeks to empower users, providing not just a means of mobility but a tool for enhancing independence and confidence. Rigorous testing and evaluation protocols are integral to the development process, ensuring the accuracy of gesture recognition, responsiveness of motor control, and overall user experience.

Transportation plays a significant role in everyday life. Moving individuals or goods from one location to another is called transportation. The import and export of goods significantly impact the country’s economy. Road transport is a crucial land transport used for importing and exporting goods. Heavy vehicles like trucks, containers, and tailors are used for transportation. Driving at night can be challenging since the vehicle’s visibility is reduced, which increases the risk of serious accidents. Even shipping goods through North India during fog and mist is more difficult for lengthy lorries. The drivers have been killed in numerous accidents in the past. The visibility of heavy vehicles must be improved to avoid accidents. Heavy vehicles employ the side lamp to increase visibility and communicate their presence to other vehicles. To set up the side lamp such that it turns on and off automatically, depending on the quantity of light. The automatic heavy vehicle indicator light system ensures great visibility in low-light conditions, increasing safety by effectively and reliably adjusting to ambient light levels through the use of an LDR-based circuit. Because of its affordability and practicality, it enhances road safety while lowering power consumption for energy efficiency.

In the pursuit of sustainable urban development, our project proposes an innovative solution that combines smart street lighting and air pollution monitoring. The first phase focuses on automating street lighting through a master-student system, where a designated master street light, equipped with light sensors, controls adjacent street lights, reducing installation costs and enhancing system efficiency. The second phase extends the project's scope to environmental monitoring, incorporating air pollution sensors into each master street light. This creates a comprehensive data network, collecting real-time air quality data for transmission to relevant authorities. Our project addresses energy conservation and environmental awareness by seamlessly integrating smart street lighting with air pollution monitoring, offering a holistic solution for creating smarter, more sustainable urban spaces.

The escalating global occurrence of borewell mishaps, particularly involving minors, prompts the development of an advanced solution. This research aims to engineer a portable robotic system, emphasizing precision, rapidity, and cost-effectiveness for efficient crisis intervention. Users direct the Rescue Robot within the well, with accuracy dependent on contextual factors. Terrain morphology and internet connectivity impact response accuracy. As rough terrains hinder mobility, smooth surfaces are crucial for optimal operation. Uninterrupted internet connectivity is paramount for Bluetooth efficacy. Safety involves a strategically positioned safety robot, mitigating further descent risk. Continuous CCTV observations enable manual control via PC or mobile. Systematic evaluation ensures adaptability to diverse environmental conditions, offering a reliable solution to borewell rescue challenges.

This review paper explores the integration of a comprehensive vehicle anti-theft system, combining fingerprint and passcode authentication with speed control and obstacle detection. The rising concern of vehicle hijacking and theft emphasizes the need for enhanced security measures within the automotive industry. Leveraging biometric systems, known for their effectiveness in diverse applications, proves to be a promising solution. Biometric systems utilize unique biological traits to identify individuals, employing algorithms to ensure accurate user identification. In this suggested system, the signals produced by the controller are directed to the relevant circuit within the module. Simultaneously, paper delves into the crucial relationship between security and performance monitoring in vehicles, emphasizing the significance of the speedometer as a vital component. Furthermore, the study advocates for the development of a cost-effective obstacle avoidance system applicable to both robots and automobiles, aiming to prevent accidents and minimize damage. This comprehensive approach combines advanced security, performance monitoring, and obstacle detection, offering a multifaceted solution to mitigate the risks associated with vehicle theft and enhance overall safety in the automotive realm.

The rising frequency and severity of fire events endangers human life and property. Firefighting is a momentous and perilous job. Fire detection and extinguishment are the hazardous job that invariably put the life of a fire fighter in danger. Traditional fire detection and extinguishing systems often face limitations in terms of speed, efficiency, and accessibility. This paper introduces an innovative solution—a Fire Detection and Extinguishing Robot designed to autonomously detect and suppress fires in diverse environments. The robot’s hardware part comprises a combination of sensors including smoke detectors, temperature sensors, and gas sensors, which enables the identification of potential fire hazards in the environment. These sensors continuously monitor the surrounding conditions and provide real-time data to the controller. The controller processes the sensor data, employing intelligent algorithms to analyse the inputs and accurately detect the presence of a fire. Upon detection, the robot employs its actuation system, which includes motors and a chemical-based extinguisher, to swiftly move towards the fire source.The robot’s mobility is facilitated by wheels or tracks, enabling it to navigate various terrains with agility. Once the fire source is reached, the robot activates the extinguishing mechanism to suppress the flames effectively. The chemical-based extinguisher, controlled by the system, releases a targeted stream of ABC powder to mitigate the fire, reducing the risk of further damage and providing immediate firefighting capabilities.

In previous times, the task of cutting or mowing grass required a significant amount of time and exertion. The introduction of a novel breed of mowing equipment significantly facilitated the task, however it remains a laborious and time-intensive activity that necessitates oversight. Individuals may personally mow the tiny lawns of their residences, however larger lawns require labor assistance. Regardless of the scenario, the task necessitates an investment of time, effort, or finances. An automatic lawn mower is the solution to this problem. It reduces the amount of time, effort, and labor expenses required. The operation of this machine is governed by an controller, which receives input from several sensors and regulates the movement and mowing procedures. In this robotic project, we will build an automatic grass cutter robot or a lawn mower robot using controller. The robot can cut the excess grass in the garden automatically. If there is an obstacle in the garden, then it will automatically change its direction. It helps to reduce human efforts. The Automatic Grass Cutting Robot is a modern solution to the labor-intensive task of maintaining lawns and grassy areas. This project aims to design and develop a robot capable of autonomously mowing grass within a predefined area using an microcontroller and an ultrasonic sensor. The robot's primary function is to navigate the designated area, detect obstacles, and efficiently cut grass using a rotary blade.

Solar panels have become more popular in recent years for converting solar energy into electrical energy. The solar panel can be used as a standalone device or as part of a larger solar array that connected to the power grid. However, most solar panels are now static, despite the fact that the sun’s location changes from time to time. This will affect the efficiency of the solar in generating energy as well as the time it takes to charge a battery if the solar panel system is an off-grid or acts as a standalone solar panel system since the solar panel can generate the maximum energy when it is perpendicular to the direction of solar radiation. As a result, the focus of this research is on the development of a standalone dual-axis solar tracker system with battery charger. A Light Dependence Resistor (LDR) Sensor is used in the proposed tracker system to sense the intensity of light and provide the output signal in analog to microcontroller. Controller will regulate the rotation of the geared DC motor through the motor driver L298N, causing the motor to rotate the solar panel based on the highest intensity of light. Test results show that the proposed dual-axis solar panel tracker system is able to capture more solar radiation, and consequently create more solar power than the fixed solar panel.

Line follower robots are autonomous robots that detect the black line by infrared ray (IR) sensors which send and receive infrared waves to identify the black line. Moving along with complicated paths such as dashed, spiral, and sharp angles requires a more appropriate configuration of the IR sensors. The goal of this study is to propose a line follower robot that can pass regular and irregular, dashed-line, and spiral paths. The structure of the robot includes three main parts: the L298 module, the programmable board, and twelve IR sensors. The black line is identified by the IR sensors. Nine sensors are used for following spiral paths, and three additional sensors are considered for passing the dashed-line paths. The sensors are configured in such a way that the robot can follow the lines and move with the least error. The speed and direction of the motors are adjusted by an L298 module and the programs are processed by the Experimental results demonstrate that the robot could satisfactorily follow the lines with high accuracy and a low tracking error.

Faced with the growing challenges of water management in agriculture, this paper explores the shortcomings of traditional irrigation methods and calls for the adoption of innovative technologies to meet these challenges. This paper proposed an innovative solution by combining embedded systems (Controllers) and environmental sensors to create a real-time intelligent irrigation system. Based on these technologies, the system automatically adjusts irrigation operations in real-time, according to environmental conditions, thus improving water use efficiency. Essentially, this study developed an intelligent system capable of dynamically adjusting irrigation based on environmental parameters, including soil moisture and water level thresholds. This approach aims to reduce water wastage while improving agricultural productivity. The methodology involves the use of an microcontroller, and advanced sensors such as temperature, humidity (DHT22), moisture, water level, and pumps as actuators. The algorithm developed enabled continuous monitoring and adaptive control of the pump, as well as data logging on the controller for real-time feedback. Tests carried out confirm the effectiveness of the smart irrigation system since it has considerably reduced water wastage while maintaining optimum agricultural productivity, compared with traditional methods. This innovative approach enables farmers to save considerable quantities of water while guaranteeing a high-quality harvest. By encouraging more sustainable farming practices, this solution contributes to the preservation of natural resources and the long-term sustainability of agriculture.

This paper proposes monitoring leakage in underground pipes using ZigBee in Wireless Sensor Networks. Leakage in underground pipes is a significant concern for water utilities as undetected leaks can result in water loss, leading to substantial financial losses and environmental concerns. The proposed system comprises ZigBee-enabled sensor nodes deployed strategically along the pipeline network. These nodes collect real-time data on various parameters such as pressure, flow rate, and temperature. By analyzing these parameters using advanced algorithms, the system can detect anomalies indicative of leaks or abnormalities in the pipeline network. To validate the effectiveness of the proposed system, simulations and experiments are conducted under various scenarios, including different leak sizes and locations. Results demonstrate the system’s high accuracy in detecting and locating leaks while minimizing false alarms.

In a shopping mart, imagine ten people waiting in line. If the first five people have many items in their carts, the last person with only one or two items may wait a long time to pay. To address this issue, we introduce an innovative Smart Trolley Billing System using controller and EM-18 RFID technology. This system automates checkout and tracks inventory in real-time, enhancing the shopping experience. By seamlessly integrating controller with RFID tags, product identification becomes instant, eliminating manual scanning. With features like an LCD screen for transparent item lists and weight sensors for added security, our solution aims to optimize shopping, improve customer satisfaction, and streamline inventory management in retail environments.

Gas leakage is an alarming problem in domesticated, industrial, and commercial environments, demanding the establishment of trustworthy and effective detection systems. This paper suggests a novel LPG gas detection model with smart tracking capabilities using controller and GSM technology. The proposed system employs gas sensors to quickly and accurately identify gas leaks by detecting the presence of potentially dangerous gasses. Upon detection, the system generates an alarm and starts immediate communication through GSM modules. The device sends SMS notifications to the appropriate authorities, such as homeowners, security personnel, and emergency services, providing crucial information about the gas leak's location. Additionally, the gadget uses GPS technology to intelligently detect gas leaks, enabling quick response and efficient remediation. Users may regulate and supervise the system without using any guidance or instructions. The performance of the system is thoroughly examined in the research, which proves its exceptional accuracy, reliability, and responsiveness in real time. By enabling the early detection, tracking, and reaction to gas leak emergencies, the recommended LPG gas detection model and smart tracking system provide a new and standardized way to enhance gas safety.

The quickest development of innovation has made our way of life solace. The innovation likewise expanded the traffic gambles and the street accidents that happen habitually which cause colossal death toll because of deficient of crisis office. To have the option to plan an item utilizing an incorporated innovation will be useful to any designing issues and an immense commitment to the local area. In the aftermath of an accident, the amount of time that passes between the incident and the dispatch of crisis clinical faculties to the scene is a strong indicator of endurance rates. Dispensing with the time between when an accident happens and when the people on call are dispatched to the scene diminishes the death rate and can save lives. Using in-vehicle programmed accident location and warning systems is one approach to eliminating the delay between accident events and expert on-call dispatch. This framework means to alarm the precious ones of the individual in the vehicle about the accident to give prompt clinical guidance. A time clinical guide can help save lives, in this system when a vehicle meets with an accident, Sensors, for example, the Accelerometer and Eye flicker sensor identify a signal in the event of an accident and convey a message to the associated microcontroller. The area of the accident shipped off the recently coded numbers so prompt assistance can be given by the emergency vehicle or the family members concerned. GSM innovation is utilized to imply the vehicle position as latitude and longitude are organized through SMS. The location is determined by the use of GPS satellites, and afterward, a message is sent to the appropriate emergency response, and subsequently, the rescue vehicle service or family members may promptly reach the location.

In the pursuit of safer roads and a more secure driving experience, our research leverages the C board to address critical issues surrounding potholes and nighttime driving challenges. Picture this: a journey where road hazards are met with swift detection, and the night sky is illuminated with intelligent and considerate headlights. Delving into the heart of the matter, the need for our research is starkly evident. Current data underscores the alarming frequency of accidents stemming from hidden potholes and blinding headlights. These incidents not only jeopardize lives but also strain economies due to vehicle damage and medical costs. It's a compelling call to action. With the controller C board, we introduce a groundbreaking solution. Our real-time pothole detection system, employing ultrasonic sensors, stands as a guardian on the road, instantly alerting drivers to potential dangers. The rationale is clear: reduce accidents, save lives, and alleviate the financial toll on individuals and governments. Simultaneously, we address the persistent issue of nighttime driving discomfort. By seamlessly integrating Automatic Headlight Dimming, guided by Light Dependent Resistors (LDR), we create a driving environment that is not only safer but also environmentally conscious. The system intelligently adapts to ambient light conditions, reducing glare, conserving power, and contributing to a sustainable future. This research paper is not merely a technical exploration; it's a commitment to humanizing road safety. It envisions a world where drivers navigate roads with confidence, where accidents are the exception rather than the norm. Our work stands as a testament to the transformative power of technology in making roads safer, driving experiences more secure, and communities more resilient.

This project introduces a School Transportation Bus Monitoring System designed to enhance the safety and security of students during their commutes. The system integrates various sensors to monitor the driver’s status, including alcohol level, eye blinking, and heartbeat. Additionally, it detects critical vehicle safety indicators such as fire and fall accidents. Environmental factors inside the bus, such as temperature and humidity, are also monitored. The system displays real-time sensor data on an LCD and triggers a buzzer alert in case of anomalies. Furthermore, it sends immediate notifications, including captured photos and location details, to the school management through an camera module. This comprehensive program is designed to provide effective and efficient solutions to keep students healthy while traveling to and from school.

The presence of visually impaired people around the globe has greatly increased due to many factors that affects the overall health of a person. In such way, this article reviews the current state of technology and aims a new way to help the people in question. It presents an assistive helmet that incorporates three essential features for the blind people to regain their self confidence through independent mobility and with all these, maintaining a low cost making it affordable for the majority. The features early mentioned are Obstacle Avoidance which will guide the person without being hurt by any sudden obstacles, Fall Detection which will produce a strident sound and light signals in order the person to be helped and, lastly, Track Monitoring which is responsible to record the path the user took.

The creation of a safety system that is based on GPS and is developed exclusively for the health and safety of women via the incorporation of novel elements in order to meet the rising concerns about crimes committed against women. The gadget is capable of contacting authorities, conveying the user’s position via SMS, and generating a loud noise to attract attention. It may be triggered in anticipation of potential danger and can be activated in the event that danger is imminent. In order to guarantee that only authorized users are able to activate the device, the system makes use of fingerprint recognition in a very unique way. Using technologies such as global positioning system (GPS), global system for mobile communications (GSM), and microcontrollers, this study makes a contribution to the continuing efforts to improve the safety of women via technological innovation. It provides a proactive approach to prevent violence against women and save lives. The research emphasizes the significance of combining hardware and software in order to provide a complete safety tool. It also illustrates the vital role that quick support plays and the potential of such gadgets to promote confidence among women in public places.

Nowadays, fuel theft is considered to be a serious problem and it creates a significant financial impact. Most of the fuel theft is from vehicles, commercial transportation containers, and industrial fuel storage containers. To prevent fuel theft and any abnormalities in the battery of a hybrid electric vehicle, an innovative hybrid model is developed where the fuel level is constantly monitored using a resistance-based fuel level sensor. The rapid change in the fuel level can be sensed by the rapid change in the resistance values. The State of Charge in the battery of the HEV/electric vehicles is monitored using a voltage sensor, any abnormalities in the SoC of the battery in the electric vehicles can be sensed with the help of voltage values from the voltage sensor. The Global Positioning System that is integrated with the Microcontroller collects the GPS coordinates of the location where the rapid change in the fuel level or the abnormalities in the SoC (State of Charge) is detected. The Microcontroller processes the collected data from the fuel level sensor and the GPS and sends an alert using the GSM Module which is being utilized for cellular communication. An onboard buzzer and the integrated display alert the personnel to the rapid change in the fuel level. The fuel level in the fuel containers or the SoC of the hybrid electric vehicles is constantly monitored and is displayed on the integrated LCD. The method of fuel theft/abnormality detection and alarm system helps in efficiently preventing fuel theft. This proposed method is deemed to be accurate, and cost-effective and contributes significantly to reducing both environmental impact and financial losses from fuel theft.

According to the Ministry of Road Transport and Highways' 2021 data, India has reported a total of 4,12,432 road accidents, resulting in 1,53,972 deaths and 3,84,448 injuries. Non-wearing of helmets has affected 1,40,356 persons, with 46,593 deaths and 93,763 injuries. Over-speeding has affected 2,95,522 persons, with 1,07,236 deaths and 2,80,285 injuries. Drunken driving or consumption of alcohol and drugs has affected 10,823 persons, with 3,314 deaths and 7,509 injuries. From this it is evident that a Smart system must be developed to reduce the accident count. The system proposed will able to control the engine based on alcohol consumption status and rider worn the helmet or not. It will monitor the speed continuously and alert the rider regarding over speeding by activating the buzzer. When over speeding count exceeds 5 times in a span of 30 days, SMS is sent to the traffic department using GSM module. Additionally Anti-theft system is also present, which activates the theft buzzer indicating the theft activity. To increase the battery backup, the frequency of the Raspberry Pico microcontroller was reduced to 25MHz from the default frequency of 125MHz. Thus, the overall system was made power efficient and convenient to riders.

The purpose of this study is to highlight a revolutionary real-time embedded finger-vein detection system that was developed for the purpose of enhancing the safety of automated teller machines. The technology takes advantage of an embedded platform and integrates a CNN algorithm for the detection of finger veins. The picture capture module which takes datasets of couple of vein images for image processing, the embedded main board that uses for the display the output and sends the message to user. The embedded main board handles processing the output that are collected from the finger veins by the image acquisition module, which is responsible for collecting the photos. For the purpose of executing the recognition algorithm and communicating with peripheral devices, this board is equipped with a communication port, memory (flash), and a microcontroller chip. That makes it easier to display the results of recognition and to receive input from members of the user community. The system, which was designed as an intelligent security solution, offers remote monitoring through internet access and provides transaction verification through the use of GSM technology. The final results showed encouraging outcomes.

Background: As the worldwide fleet grows, there is a greater demand for effective vehicle monitoring systems. Traditional car monitoring tools, although accessible, have been regarded as expensive, complex, or both. Objective: The primary purpose of this article is to create and construct an efficient car tracking system utilising controller that combines GPS and GSM technologies. This system intends to provide SMS updates of a vehicle's location and real-time tracking capabilities on a user's smartphone. Methods: The tracking device's hardware includes an microcontroller, a u-blox NEO-6Q GPS module, and a u-blox LEON-GIOO GSM module. Using GPS coordinates, the system utilises the GSM module to communicate live location updates to a user's phone, enabling them to see their vehicle's precise position on Google Maps. Results: The proposed tracking system provides a cost-effective and versatile solution that is notably useful for fleet management, public transit, and individual automobile owners. Its use offers excellent driving safety, increased public transit efficiency, and streamlined fleet operations. Conclusion: GPS and GSM-based vehicle tracking technologies, as shown in this work, have changed the field of vehicle monitoring. The integrated technologies enable customers to remotely monitor their cars, which improves safety, operational efficiency, and cost-effectiveness.

One of the primary causes of auto accidents is speed. Numerous lives may have been saved if rescue workers had been able to get accident information and get there in time. The accident detection systems that are the subject of this research utilize many components in order to detect accidents and alert rescue personnel when help is needed. An efficient automated accident detection system that instantly alerts emergency services to the accident's location is crucial for protecting people's precious lives. The recommended approach deals with accident identification and notification. After reading it, it sends the afflicted vehicle's exact latitude and longitude to the emergency response provider closest to you. The project's objective is to find incidents and notify the rescue squad as soon as feasible.

The process of energy management requires innovative solutions to monitor, safeguard, and optimize electricity consumption. In response to this demand, this study proposes an advanced Electricity Theft Detection and Alert System that leverages state-of-the-art technology for real-time monitoring and user awareness. The proposed system integrates various components, including voltage and current sensors, a secondary current transformer (Transformer-2), an energy meter, GSM communication, and an microcontroller. Through continuous monitoring, the proposed system calculates the unit consumption of electricity and transmits this information to the user's mobile number via SMS. Notably, it employs a sophisticated theft detection algorithm to identify irregularities in voltage, current, and energy consumption, triggering immediate alerts in the event of potential theft. Safety mechanisms, such as automatic shutdown during overloading or voltage fluctuations, further enhance the system's reliability. The proposed system not only empowers users with real-time insights into their power usage but also acts as a proactive guardian against unauthorized access and electrical anomalies. The obtained results highlight the proposed system's effectiveness, with illustrative tables presenting dummy values to showcase its functionality.

1.35 million people die every year due to road accident including cyclist. One of the main reason that contribute to this statistic is delayed response by the rescue team. This project aims to detect the precise location of the victims as well as to notify their next-of-kin immediately about their status. A GPS module, TTGO T- Call with built-in GSM Module and 3-Axis Accelerometer are used to develop the project prototype. The accelerometer sensor detect any fall and send the location of the fallen cyclist to the next-of-kin via SMS. This project benefits the cyclist to get immediate assistance in case of any mishap that is not within the vicinity of other road users

Child harassment and abduction pose significant threats to the mental and emotional well-being of children in today's society, exacerbated by their lack of awareness of potential dangers. To address this challenge, this proposal advocates for the development of a dedicated mobile application and tracking device aimed at preventing instances of child harassment and enhancing safety measures for children aged 5 to 12. The application, in conjunction with the tracking hardware device, forms a protective barrier around children, providing real-time monitoring and sending regular notifications to parents regarding their child's whereabouts. Immediate alerts are triggered upon the child's departure from or arrival at designated locations, such as home or school. Beyond the primary target demographic, the application caters to various stakeholders invested in child safety, including parents, teachers, caregivers, and individuals responsible for children's well-being. By promoting awareness, enabling real-time monitoring, and providing immediate assistance in distressing situations, this innovative mobile application aims to bridge the gap between children's vulnerability and their safety, empowering them to navigate the world with confidence. Ultimately, the objective is to promote a safer environment, where children can thrive without fear, while equipping caregivers with the necessary tools to ensure their protection.

Proper indoor air quality (IAQ) not only prevents health issues but also enhances cognitive function and overall satisfaction. In this work, we propose a wireless sensor network for CO2 measurement in large buildings, such as schools. We have developed ultra-low-power and cost-effective sensor nodes that consume an average current of 130 μA when gathering measurements at a 30-second rate, and effectively transmitting them to a server for analysis and visualization. We present field measurement results from the WSN operating in a school for over six months. Finally, we compare our system with similar state-of-the-art systems and demonstrate outstanding performance in terms of power consumption.

This project aims to develop a fire alarm-based obstacle-avoiding and Bluetooth-controlled robot. The robot is designed to detect fires, navigate its environment while avoiding obstacles, and be controlled remotely via Bluetooth. By combining these features, the robot can autonomously detect and respond to fires while providing a convenient means of control. The hardware components of the robot include a chassis, wheels or tracks for mobility, motors, a microcontroller or single-board computer, fire sensors, obstacle detection sensors (such as ultrasonic or infrared sensors), and a Bluetooth module for wireless communication. The fire detection system is responsible for monitoring the environment and triggering an alarm or alert when a fire is detected. The obstacle avoidance system utilizes sensors to detect obstacles in the robot’s path and employs appropriate maneuvers to avoid them. By combining these features, the robot can autonomously detect and respond to fires while providing a convenient means of control. In autonomous mode, the robot operates independently, detecting fires and navigating obstacles. In manual mode, the user can direct the robot’s movements and control its actions using a Bluetooth-enabled device.

This study presents an automatic curtain opener robot, which can be configured using a smartphone for hotel establishments. Users have the flexibility to open the curtain either at specific points or entirely. Additionally, the device can be programmed to open the curtains automatically based on preset times. A microcontroller controls the overall functionality of the device. Here, a mobile app was created using MIT App Inventor and is essential for operating the various control features. The app requires Bluetooth connectivity with the device for the configuration. Testing involved the connectivity between a smartphone and the device, the response of the device to the specified preset times, and its performance in manually opening and closing the curtain through the application. The results demonstrate a 100% accuracy rate for manual operations. Furthermore, the device successfully connected with all tested Android phones. Evaluation was also conducted to assess the developed robot’s accuracy in opening the curtain based on distance, yielding a 99.22% accuracy rate from the tests.

Drip irrigation systems have become an integral part of modern greenhouse farming practices as they help irrigate plants effectively and also supply plants with water and nutrients in precise amounts. Nevertheless, these technologies have to be perfectly adjusted to efficiently utilize water and boost crop yield. This research addresses two issues: firstly, the capacity of the sensing technology innovations for greenhouse drip irrigation to be more efficient, and secondly, sustainability. The study looked for several types of sensors and materials that can be used in the construction of the system section that take into consideration the information from the intelligent sensors and the monitoring of environmental parameters. The methodology used in the study was a methodological review. This paper will discuss the literature dealing with different mechanisms, tools, and materials to control environmental factors that could affect the drip irrigation system in greenhouses. The literature review presented several types of sensors, including temperature sensors, soil moisture sensors, and humidity sensors, which are the key components for intelligent greenhouse drip irrigation systems operating correctly. Embedding these sensors and materials in a comprehensive system has exhibited a positive effect on water consumption reduction and nutrient uptake by plants. The results of the discussion stress the high sensitivity to the choice of materials and sensors which consequence can be the deployment of the system for a long time and its high performance. Looking at the results, it is accordingly determined after the fact that sensor type and sensor materials constitute an essential part that would aid in achieving the best results with smart greenhouses through drip irrigation systems. These technologies ensure precise environmental monitoring and resource management, offering a pathway to sustainable and high-yield agriculture. The findings collected from this literature review can greatly push forward the latest demands for smart farming in the future

Smart manufacturing demands industrial that encompasses components such as sensors, industrial control systems, programmable logic controllers, gateways, wireless devices, machine series connection modules, and edge computing hosts. However, these components often use different communication protocols, and collecting, transmitting, and integrating device source data. In this study, data regarding a coating process were collected and transmitted to a data server in real-time over Bluetooth for presentation and storage. The data were then processed and analyzed to optimize production. Specifically, a supervisory control and data acquisition (SCADA) system based on Bluetooth low energy (BLE) modules was developed. The system comprised a self-developed BLE gateway that interfaced wirelessly with multiple self-developed Bluetooth devices for collecting equipment and sensor data. These devices used the Modbus TCP or RTU protocols to collect sensor data, and converted and transmitted the data to the data server. Subsequently, the data were displayed, stored, and analyzed by the graphical control system, improving manufacturing efficiency.

This paper aims to design an intelligent algorithm that tracks the maximum power from the photovoltaic system to drive a separately excited DC motor. Three algorithms were studied, namely: perturbation and observation, Sugino-based fuzzy logic control, and adaptive neural fuzzy inference system (ANFIS). The dynamic performance evaluation of the maximum power point tracking unit as well as the grid photovoltaic DC motor speed control was carried out using Matlab-SIMULINK. The proposed photovoltaic system was found feasible to generate the electricity needed to run the DC motor. The results of the simulation showed that the ANFIS-based controller is more robust than other algorithms in terms of obtaining a higher power rating, lower oscillations and reaching a steady state in a short time.

Road traffic accidents remain a significant global concern, necessitating innovative solutions for accident prevention. This paper introduces a Smart Embedded System for Accident Pre-Alert and Prevention Using Microcontroller designed to mitigate road safety risks through real-time accident pre-alerts and prevention measures. It integrates various sensors, including heart rate, ultrasonic, MEMS, eye blink, and alcohol sensors, along with an microcontroller for data acquisition and processing. Additionally, the system incorporates GPS and GSM modules for location tracking and communication Embedded programming language.

To achieve high reliability, fault-tolerance techniques are exploited, but they may increase power consumption and temperature beyond safe limits. Therefore, power-aware fault-tolerance techniques should be used to manage power and temperature issues. We tolerate both permanent and transient faults through hybrid fault-tolerance techniques. In this letter, at first, we investigate how much power and temperature are increased when a hybrid fault-tolerance technique is applied to multicore embedded systems. Then, we propose a peak-power-aware hybrid fault-tolerant technique to meet the temperature constraint. Transient-temperature-based safe power (T-TSP) is a new power budgeting technique whose calculation is based on the current temperature of the processing core. Assigning dynamic budgets through T-TSP to processing cores allows us to effectively reach the full performance of processing cores. Experiments show that our proposed method reduces peak power and energy consumption on average by 13.5% (up to 50.7%) and 41.8% (up to 67.4%), respectively and improves the schedulability on average by 6.8% (up to 22.4%) compared to state-of-the-art methods while meeting the system reliability target.

Ensuring the safety of cyclists navigating city streets remains a pressing concern, especially with the increasing frequency of accidents in densely populated areas. In fact, urban landscapes pose numerous challenges, including intricate road networks and heavy vehicular traffic, elevating the risk of accidents involving cyclists. This paper proposes the MobiAlert, an embedded system that utilizes geospatial data to evaluate the safety of cycling in urban areas. By analyzing the proximity to emergency response infrastructure and taking GPS coordinates, MobiAlert indicates the current risk level that a bicycle is experiencing, offering cyclists real-time alerts when crossing more critical areas. Implemented on a Raspberry Pi Zero board, MobiAlert is a cost-effective and efficient solution adaptable to diverse urban settings, allowing easy reproduction. Initial experiments based on the city of Porto, Portugal, demonstrates the practical applicability and effectiveness of this approach in enhancing safety for cyclists and promoting sustainable mobility.

The purpose of this research is to develop an innovative Suspended Floating Bag (SFB) for military load carriage which is meant as a solution to problems associated with conventional backpacks. This excess weight exposes infantry soldiers to higher levels of energy expenditures associated with decreased performance. This load is controlled by one of the mechanisms used in the SFB which comprises springs, pulleys, and elastic ropes that suspend and minimize the vertical displacement thereby reducing movement within the structure. In addition, these products feature a lightweight and strong frame coupled with rack and pinion for enhanced stability and precision. Real-time location tracking and anti-theft function supported by embedded technologies such as controller, Global Positioning System (GPS), Global System for Mobile Communications (GSM) modules, and buzzer system. Furthermore, it is also fitted into a self-sustaining power generation system by way of a rack and pinion as well as a dynamometer. Reduction in vertical excursion and total ground reaction force during field trials provides an enduring solution and diminishes the likelihood of conventional back pain. The research has thus made progress in the development of load carriage systems that could improve endurance as well as the comfort of military forces during critical engagements off the battlefield.

A system of embedded is a computer system built specifically for an embedded application. An embedded system, as opposed to a general-purpose computer like a personal computer, performs one or a few tasks that are pre-defined and typically have extremely specific requirements. Because the system is specifically designed to perform that task, design engineers can optimize it to make the product smaller and less expensive the electronic voting machine (EVM) is now being introduced. The use of Electronic Voting Machines (EVMs), often referred to as offline E-Voting, is strictly enforced in India. EVMs offer a variety of customizable properties, such as simple usage, dependability, and quick access. Election-related reports of irregularity are attributed to EVMs. The aforementioned criticisms serve to undermine the primary objective of voters, while the responsibility of conducting free and fair elections rests upon the Election Commission. A voting machine refers to a comprehensive assemblage of mechanical, electromechanical, or electronic components employed for the purpose of ballot definition, vote casting, and vote counting. Additionally, it facilitates the efficient recording and display of election results, preserves audit trail data, and can be readily supplied with the necessary firmware, documentation, and software required for equipment control programming. While mechanical early voting machines were used, electronic voting machines are becoming more and more common. A biometric sensor like a fingerprint reader is one of the most secure voting mechanisms because it is essential that no fraudulent entries are created.

Rapid expansion in the quantity and variety of solid and hazardous waste because of ongoing economic development, urbanization, and industrialization is posing a growing challenge for national and municipal governments to ensure efficient and long-term waste management. As reported by the Global trash Management Market Report 2007, the total amount of municipal solid trash produced globally in 2006 was anticipated to be 2.02 billion tons, a rise of 7% annually since 2003.To reduce the risk to patient and public health and safety, as well as environmental risk, waste management, transportation, and disposal must be carefully handled. Waste is best able to achieve its economic value when it is separated. There is currently no system in place for households to separate dry, moist, and metallic garbage. In order to send home waste directly for processing, this work suggests an Waste Segregator Robotic (WSR), which is an affordable, simple-to-use alternative. Its purpose is the process of separating the waste into dry and wet waste. Capacitive sensors are used by the WSR to differentiate between wet and dry trash, trash level detection, foul smell detection, relocation of the system and send alert to the person in-charge. Experimental findings demonstrate that the WSR has successfully integrated the separation of waste into moist and dry waste. Send an alert to the person in-charge for various issues such as trash level capacity, presence of foul smell and relocation of the system.

An RFID attendance-based system is a prototype that uses Radio Frequency Identification (RFID) to track and monitor the attendance of individuals. The system uses RFID tags, that are electronic systems that contain unique identification information. These tags are to be fit to objects or worn by individuals, such as employees, students, or attendees and are identified by an RFID reader. The RFID attendance-based technique is a contactless system that eliminates the necessity for manual attendance tracking and provides a more accurate and efficient method of recording attendance. The system allows for tracking of attendance and can provide instant notifications to authorized personnel regarding attendance status. Overall, the RFID attendance-based system provides a reliable and convenient method of tracking attendance, which is placed in a variety of settings, such as organization, workplaces, and events. These use RFID prototypes to capture students' data as they enter or exit the classroom. This paper presents an abstract of an RFID-based student attendance unit that can be used in educational institutions. The proposed prototype has high accuracy, efficiency, and security of attendance tracking, thus reducing the burden on teachers and administrative staff. The system comprises RFID readers, RFID tags, a database, and software for analysis. The RFID tags are embedded in student ID cards, which are scanned by RFID readers installed at the arrival or exit of the classroom. The attendance is transferred to the database, where it is stored and processed for generating reports and alerts. The system has many advantages reducing absenteeism, improving student engagement, and enhancing overall academic performance.

Voice control-based systems have become the ubiquitous means of communicating with smart devices. This has led to massive expansion in adoption of home automation systems by many households. In this paper, a speech recognition-based module is utilized to record and process the voice-based speech commands,that are converted to text data. The controller system with Bluetooth connectivity serves to handle the voice commands and allows for controlling of gadgets such as lights. The controller based microcontroller system utilizes the natural language processing techniques to create a voice-activated home automation system allowing the house owners to operate a variety of electric and electronic gadgets and appliances. The controller connects with the respective applications using communication protocols.

This paper gives an overview of challenges introduced due to the interconnection of distributed generators into the grid. It also discusses the control technique and scope of applications in the mitigation of power quality issues. Exhaustive discussion is carried out on the interconnection of DGs to the grid and power quality issues. It also discusses the different controllers and algorithms that are used to control the parameters of the distributed generation system. A detailed comparison of conventional controllers studied by authors that are used in distribution generation is also discussed. Similarly, the application of artificial intelligence and adaptive algorithm in distribution generation is also presented as per the points, Different connection methods of DG’s to the grid, the effect of distributed generation on power quality, the necessity of local voltage control of distribution generator, control methods and intelligent techniques.

Fire is a very dangerous situation that needs to be prevented before something out of the ordinary happens. It is imperative to monitor fire conditions closely; otherwise, this may result in numerous property and human losses. One of the essential and significant uses of fire detection and fire hazard prevention. It can identify fires early and notify fire control centers. This paper proposes a smart fire detection and control system that uses temperature, smoke, flame, LDR, and MQ2 sensors to determine the fire's speed and intensity. In addition to transmitting the most recent situational information, this proposed system-based fire monitoring and control system also takes the required corrective action. The controller board serves as the building block for the fire alarm system, relaying information to fire control centers and setting off the alarms in accordance with the intensity of the fire. The system will trigger an alarm and send a notification to the fire control centers, whenever a flame is detected and has the potential to spread. Depending on the intensity of the fire, the fire extinguisher and water sprinkler will activate simultaneously.

The increasing demand for efficient and sustainable agricultural practices has led to the development of advanced technologies in the field of precision agriculture. In this paper, the design of a Soil Moisture Monitoring and Seed Sowing Robot is proposed. This system helps to enhance the seed-sowing process in agricultural applications. This robotic system integrates the capabilities of the microcontroller and servo motor to optimize the seed-sowing process. Additionally, it incorporates a moisture monitoring system to continuously assess soil moisture levels and send that data, ensuring optimal growing conditions. This paper highlights the design, implementation, and testing of the Smart Agriculture Seed Sowing Robot, featuring technical specifications, operational workflow, performance evaluation, and real-time soil moisture monitoring. The results demonstrate the effectiveness and potential impact of this robotic system in modern agriculture, paving the way for further advancements in precision farming techniques.

The efficient movement of ambulances is crucial for timely response and effective emergency management in urban areas. However, congested road networks often impede their progress, leading to potentially life-threatening delays. It presents an innovative solution: an automated traffic system for emergency vehicles utilizing RF (Radio Frequency) modules. By harnessing RF technology, this system enables seamless communication and coordination between ambulances and the road infrastructure. Real-time vehicle identification, intelligent traffic management, and enhanced safety measures are key features of this system. By dynamically managing traffic flow, optimizing signal timings, and granting priority access to ambulances, the system minimizes response times while minimizing disruption to regular traffic. Moreover, the integration of RF modules paves the way for future advancements, including predictive routing and adaptive traffic management. The implementation of this automated traffic system holds immense potential to revolutionize emergency response, enhance road safety, and save lives in our increasingly complex urban environments.

This work introduces an independent smart irrigation setup employing Controller . Through sensors monitoring soil moisture, temperature, and humidity, it manages irrigation by controlling a water pump and solenoid valves. Integration with allows scheduling and notifications for remote accessibility. The system's primary objective is to conserve water while ensuring optimal soil moisture levels, fostering agricultural benefits such as increased crop yield, reduced costs, and sustainable practices. Operating between 9 to 12 volts DC, it utilizes soil probes to gauge moisture content. Upon detecting insufficient moisture, the Controller triggers the relay, activating the pump to irrigate the crops. This innovation minimizes manual labor, enhances water efficiency, and proves economically viable.

This paper mainly focuses on the design and development of a low-cost automated wheelchair for the patient or patient attender or differently abled person. The entire system is designed based on 24 V operating voltage. The various components/modules such as Permanent Magnet DC motors (PMDC motor), linear actuators, H bridge DC-DC chopper, DC voltage regulator, Microcontroller, keypad, and Bluetooth modules are selected as per the design. An eight-channel relay module is used as an H bridge circuit for linear actuator movements in order to move the left leg footrest, right leg footrest, and back supporting rest independently. Simulation of four quadrant chopper is carried out with an equivalent PMDC motor load to analyze the electrical parameters such as switching pulses, voltage across motor & current drawn by the motor using the MATLAB/Simulink software package. The hardware modules are mounted on the wheelchair and coupled to two PMDC motors and six linear actuators. The input voltage across the motor and current drawn by the motor are recorded using a power quality analyzer HIOKI PW3198 model. The waveforms and results obtained from the simulation of the power converter are in conformation with the hardware results obtained. The navigation mode, left leg footrest, right leg footrest movements, and reclining of the wheelchair are tested independently by using a switch selector to choose either keypad mode or Bluetooth mode and found to be successful with respect to the features considered for the design of the automated wheelchair.

This paper introduces a ground breaking Smart Motion Detection and Location Tracking System designed for enhanced security in homes and offices. Unlike conventional motion detectors, this system integrates Global Positioning System (GPS) technology with Passive Infrared (PIR) sensors, providing not only motion detection but also accurate direction determination. The synergy of PIR sensors and GPS enables a more sophisticated understanding of movement patterns, offering real-time location tracking and direction identification. This innovative approach allows for a nuanced response to security threats, making it particularly valuable for security personnel or automated systems. The system's ability to combine motion detection with precise location data revolutionizes security applications, offering a comprehensive solution for advanced threat identification and response.

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 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 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.

A knowledgeable management system based on a single integrated device is developed for the automobile lighting system in order to enhance the smart operation of vehicle headlamps and increase the security and dependability of vehicle driving in a wide range of weather conditions, particularly with dust, fog, and haze. When driving at night, the vast majority of drivers turn on their brightest beam. The inconvenience this provides to the individual coming from the opposite route is obvious. To prevent such occurrences, two vehicles are needed to demonstrate the proposed system, which uses a Light Dependent Resistor (LDR) sensor and related communication to help drivers avoid collisions by adjusting their high beams in response to oncoming traffic. To prevent this glare, engineers devised a prototype automated headlamp intensity adjustment system. People driving at night are temporarily rendered blind by this beam, increasing the risk of collisions. When it detects an oncoming vehicle, the high beam automatically changes to the low beam. The manual switching by the driver is unnecessary thanks to this model’s philosophy. The primary objective of this technology is to use an controller to control the vehicle’s headlights in a sophisticated manner, taking into account ambient light levels via a resistor that depends on light and the presence of oncoming traffic via an ultrasonic sensor. Consequently, the system automatically controls the strength of the car’s headlights and establishes an appropriate intensity quality throughout the night, taking into account the ambient light level and the presence of a vehicle approaching from the opposite way.

Radio direction finding, traditionally used for localizing radio signal sources, has been adapted for Bluetooth to enable indoor localization of wireless devices. This adaptation is particularly relevant for achieving accurate indoor localization within networks, especially in battery-powered and resource-limited embedded systems. However, the intricacies of implementing direction of arrival (DOA) methods in such systems, notably those lacking a floating-point unit (FPU), present significant computational challenges. This article addresses these challenges by introducing an innovative fixed-point DOA method, rooted in the estimation of signal parameters via rotation invariance techniques (ESPRIT). Diverging from traditional complex eigenvalue decomposition, our approach employs a simpler power method for DOA estimation and phase offset compensation, utilizing a straightforward trigonometric equation. It also integrates an improved carrier frequency estimator, also based on ESPRIT, which is tens of times more accurate than the conventional method of averaging phase differences. We conducted bare-metal level experiments on an nRF52840 system on chip to evaluate execution time, memory footprint, angle accuracy, and energy consumption. The fixed-point implementation demonstrated an execution time of 2.3 ms and an energy consumption of just 0.348 nWh. These figures represent a 5.9-fold increase in energy efficiency and a 4.4-fold improvement in speed compared to the conventional software-based floating-point approach while maintaining an angle accuracy ranging from nearly 2° to under 0.5°, depending on the signal-to-noise ratio. However, in IoT devices equipped with an FPU, the hardware-based floating-point technique still edges out, being 0.8 ms faster and slightly more energy efficient at 0.319 nWh.

The wearables involve small embedded devices with sensors collecting data from their surroundings. Nowadays, people have added complexity as well as busyness to their lives and they do not give their health much thought due to their hectic routines. Current health monitoring systems are often cumbersome and inconvenient for patients, leading to poor adherence and delayed detection of health issues. To address this problem, heart rate oxygen rate temperature watch (HOT Watch) an IoT-based wearable health monitoring device has been proposed to track the user’s health condition and notify the person with their health details. The HOT Watch employs sensors, such as the MLX90614 temperature sensor, AD8232 electrocardiogram (ECG) sensor, and MAX30100 oximeter sensor to gather health metrics from users. The HOT Watch employs controller technology and Bluetooth connectivity to transmit data to a mobile application and the Pan-Tompkins algorithm (PTA) precisely determines the user’s heart rate. The proposed method displays the essential health information and alerts users about their health status, including the location data obtained from the GPS sensor in the watch. By continuously tracking vital signs such as temperature, oxygen saturation, and heart rate, individuals can gain valuable insights into their overall health status. These real-time data allow users to monitor their well-being proactively and make informed decisions about their lifestyle and activities. The accuracy of the proposed HOT Watch is 1.40%, 0.70%, and 2.47% higher than the existing Sensor Patch, IoT-based wearable sensor and Neo Wear, respectively.

Vehicle tracking systems have evolved significantly over the years, transitioning from simple passive tracking devices to real-time monitoring systems that utilize global positioning system (GPS) and global system for mobile communications (GSM). These advancements have enabled more precise tracking, better communication capabilities, and enhanced control over vehicle operations. Despite these improvements, there remains a persistent need for systems that are not only reliable but also incorporate multiple layers of security to prevent unauthorized access and use. This research paper introduces GPS and GSM based tracking system designed to significantly enhance vehicle safety and provide real time location monitoring. The system utilizes an controller as the primary control unit, interfaced with a GSM module (SIM800L) for communication and a GPS module (NEO-6M) for precise tracking of the vehicle's location. Key components include a relay-controlled ignition switch and a key lock system to manage vehicle startup, a fingerprint sensor for advanced biometric authentication, and a buzzer for auditory alerts. The entire system operates on a 9 V power supply, with voltage regulation managed by an LM2596 step-down converter. This integration of hardware components ensures robust vehicle tracking, remote control capabilities, and heightened security measures, thereby offering an effective solution for personal vehicle safety and efficient fleet management. In an average, for every 10 iterations we observed that 9 iterations are where successful, which shows that the efficiency was 90 % as there was delay in sending and receiving messages.

Recently, the demand for in healthcare systems such as healthcare monitoring, fitness programmers, etc. has grown significantly. Healthcare monitoring devices play an important role in health data measurement and collection. In this paper, the system integrates for healthcare monitoring. The proposed system can measure, monitor, and report people's health data in real time. The proposed system has been designed with a Raspberry Pi to measure and monitor body temperature, heart rate, oxygen saturation, room temperature, room humidity, and illumination intensity, and transmit those data to the cloud platform via the MQTT protocol. The proposed system integrates cloud computing and the IoT to deliver healthcare data in an interoperable format, which provides many advantages, including high reliability, high efficiency, virtualization, and scalability.

With progress, intelligent home care system has become a key solution to deal with the aging society. This paper studies the design and implementation of the system, aiming at improving the quality of life and health monitoring of the elderly. By analyzing the needs of home care, a comprehensive system architecture is proposed, which integrates environmental perception, data analysis, intelligent decision-making and human-computer interaction. In this paper, the system components and their collaboration mechanisms are described in detail, and their effectiveness is verified by experiments. The article covers requirements analysis, design, technology selection, software and hardware development, integrated testing and other links. The case study method is used to show how the system provides real-time monitoring, emergency rescue, health management and social interaction. This paper also discusses the problems of privacy, security and user acceptance faced by the system, and puts forward corresponding countermeasures, which not only deepens the theory of intelligent pension, but also guides the development and application practice of related products.

Fingers pulse oximeters have become health devices more and more necessary for patient monitoring, whether constant or for a short period without practically having to touch them. Right now, there are perfect solutions on the market. Still, doctors have detected some minor problems that make the essential operation of these devices difficult due to some factors, whether external or from the patients themselves. Therefore, we try to fix it so that it can be an even better product and that we do not have to consider these factors that can waste time on other, more important things. For this reason, this article presents an improvement by using excellent low-cost and quality-priced materials and adding new sensors to consider these difficulties and produce an amazing, finished product. Our proposal can determine if the device is correctly used and take those measurements to send them an App installed on a Smartphone. With this, it will be easier to monitor users and determine if that patient suffers some problem.

Indoor navigation is a foundational technology to assist the tracking and localization of humans, autonomous vehicles, drones, and robots in indoor spaces. Due to the lack of penetration of GPS signals in buildings, subterranean locales, and dense urban environments, indoor navigation solutions typically make use of ubiquitous wireless signals (e.g.,WiFi) and sensors in mobile embedded systems to perform tracking and localization. This article provides an overview of the many challenges facing state-of-the-art indoor navigation solutions

Many remote power lines do not have enough wildfire surveillance to enable preventive or mitigation measures, resulting in massive destruction in the incidence of wildfires hitting power lines. This project seeks to build a multi-sensor-based embedded system that monitors wildfire-related weather conditions to assess the risk and alert the appropriate fire management team, via a wireless data transfer protocol in case of outbreaks. The design of the system will prove useful at power stations where other safety features are incorporated to reduce the occurrences of fires. The embedded system works based on a Hot-Dry-Windy index that monitors fire weather conditions that directly affect the spread of wildfires.

This research presents the design and implementation of an integrated safety system for vehicles aimed at enhancing road safety, deterring impaired driving, mitigating rash driving behaviors, and preventing vehicle theft. The alcohol detection component utilizes an MQ3 sensor to accurately measure alcohol concentration in the driver's breath. When the concentration exceeds predefined thresholds, the system triggers appropriate responses, including engine immobilization and alerts. Rash driving behaviors are detected using accelerometers and gyroscopes, which analyze vehicle motion data in real-time. An engine locking mechanism immobilizes the vehicle's engine in response to detected alcohol presence or rash driving behaviors, enhancing safety and preventing further operation of the vehicle. GPS tracking enables real-time monitoring of the vehicle's location and transmission of location data to designated contacts or authorities in emergencies, accidents.

This brief presents an overload control scheme for hybrid AC/DC power system security enhancement by utilizing the flexible controllability of the embedded HVDC. Sensitivities of AC line power with respect to the embedded HVDC are deduced based on the structural characteristics of the grid, predetermining transmission lines that can be effectively adjusted by the embedded HVDC. The overload control of the embedded HVDC system is then proposed based on flexible DC power adjustment and AC/DC interaction. Overloads can be quickly relieved through real-time emergency power support, avoiding further risks that may threaten system security and reliability. Simulations under the IEEE 39-bus system with the embedded HVDC prove the effectiveness of the proposed control, realizing the rapid elimination of potential overloads and higher regulation capabilities of the hybrid AC/DC power system.

Road accidents remain a significant global concern, often resulting from over speeding and human error. Implementing an effective collision avoidance system is crucial for enhanced road safety. This project proposes Radio-Frequency Identification (RFID) technology combined with an embedded system to develop an anti-collision speed control system. Utilizing passive High-frequency Radio Frequency identification tags and an microcontroller, the system detects potential collisions and dynamically adjusts the speed of vehicles or robotic objects to prevent accidents. Specifically, industrial robots equipped with an embedded microcontroller and passive RFID tags can detect nearby robots and vehicles, allowing the system to modulate speed and navigate steep and sharp turns in mines safely. This capability extends to detecting turns and steep gradients in mining fields round the clock. The proposed system aims to enhance collision detection accuracy, improve response time and adaptability to changing environments.

India is a democratic nation where elections are heavily influenced by the voting method. The foundation of any social equality is the legitimacy of citizens’ selection of their own representatives. This implementation of electronic voting technology, which includes biometric authentication in restricted hardware environments. The design efficiently tackles resource scarcity associated with embedded systems while guarding robustly against meddling and unauthorized access. It elaborates on the structure, integrating biometric sensors, secure communication practices, and agreement mechanisms with block chain frameworks. Moreover, it discusses the application of voter authentication, the voting interface, and auditing processes to check election results. This proposed system propels forward the development of secure electronic voting systems and proves to be a hopeful prospect for democratic processes in this rapidly digitalizing world.