Volume 13 | Issue 7 |

 Abstract

This project is related to the invention of a vehicle security and monitoring system that integrates geo-fencing and real-time tracking. Through the use of Arduino Mega 2560, GPS, GSM, and sensors, the system offers theft detection, accident monitoring, and secure access control. In geo- fencing, boundary alerts are obtained, and, whereas, load monitoring is unauthorized use. The system fuses various security technologies executing an excellent and cost-efficient solution for both fleet management and the use of passive theft prevention, along with real-time vehicle tracking

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Geo-fencing, Vehicle Security, Theft Detection, Accident Monitoring, Boundary Alerts, Load Monitoring

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research presents an autonomous surveillance rover for defense applications designed to enhance real-time enemy detection and situational awareness. The system is powered by a Raspberry Pi, enabling centralized control and processing of data from various sensors. Ultrasonic sensors ensure obstacle detection, while inductive proximity sensors identify landmines and explosive devices. A camera module provides real-time video streaming, which is analyzed using image processing algorithms to classify individuals as authorized or threats. When a threat is identified, the system triggers a laser module to simulate a defensive response. The rover autonomously navigates its environment, continuously scanning for hazards and relaying real-time alerts to defense personnel via a communication module. This integration of IoT, artificial intelligence, and robotics makes the rover a reliable and efficient solution for modern defense challenges. The project highlights its potential to enhance security, reduce human risks, and adapt to evolving operational demands.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Autonomous surveillance, enemy detection, real-time monitoring, Raspberry Pi, obstacle detection, image processing, IoT, defense robotics.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Wildlife Observation Robot represents an innovative solution for automated forest surveillance and protection. This autonomous system integrates advanced computer vision capabilities with robust hardware components, all controlled by a Raspberry Pi microcomputer. The robot continuously patrols forest areas, utilizing a rotating camera system and Ultrasonic sensors for comprehensive environmental monitoring. Through OpenCV-based image processing, it can detect both wildlife presence and potential fire outbreaks in real-time. Upon detection, the system immediately alerts relevant authorities via Telegram messaging, providing crucial information including precise location coordinates and photographic evidence. This implementation significantly enhances forest management capabilities while reducing human intervention in potentially dangerous situations.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Autonomous Wildlife Monitoring, Smart Surveillance System, Automated Alert System

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The usage of chemical herbicides is common in the labor-intensive agricultural process of weeding, which can be hazardous to both human health and the environment. The YOLO (You Only Look Once) model is an autonomous weed identification robot that uses computer vision and machine learning to overcome these obstacles because of the robot's accurate weed identification and categorization, less chemical pesticide is used, labor costs are decreased, and sustainable farming is promoted. The method involves designing and building a prototype robot, training and testing its algorithms, and evaluating how well it performs in real-world situations. Anticipated outcomes include enhanced weed management, cost reductions, higher productivity, sustainability, and advancements in agricultural technology. This creative method combines automation and AI-driven decision-making to revolutionize conventional farming methods.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

IoT in Agriculture, Crop Health Monitoring, Autonomous Weed Identification, Agricultural Robotics, and Weed Management.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

As the demand for eco-friendly solutions grows, the EcoNav Drone offers a smart and sustainable approach to both aerial navigation and plant health monitoring. Equipped with GPS for navigation and a camera for real-time data collection, the drone operates with manual control. The SpeedyBee F405V3 flight controller ensures stability and adaptability in various environments. With intelligent route planning and adaptive flight control, the drone operates efficiently while consuming less power. In addition, early detection of plant diseases is vital for maintaining crop health and boosting agricultural productivity, making the EcoNav Drone a valuable tool for sustainable farming practices.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Adaptive flight control, Aerial data collection, Autonomous navigation, Eco-friendly drones, Energy-efficient flight, Environmental monitoring, GPS-based navigation, Low-power UAV, Optimized route planning, Sustainable drone technology.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The proposed Smart Pepper Spray is an advanced self-defense device that provides personal security through the integration of modern technology in contrast to traditional pepper spray the device includes GPS tracking and a high-resolution camera which monitors location surveillance in real time and provides visual evidence of emergency visual evidence the device is equipped with a sensor that provides GPS - as sow which GPS-as sow uses the amount spent record and store integrated cameras and film material from incidents that may serve as important evidence for film enforcement agencies compact and user-friendly design ensures portability and user-friendly while operating the system for long-term reliability with a rechargeable battery.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Snart Pepper Spray, Microcontroller ESP8266, Push Button, Servomotor, Bluetooth Module HC-05, Web Camera, Charge Controller Module.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project presents a Traffic Rules Violation Detection System using Raspberry Pi, Pi Camera, and a sound sensor. It detects unauthorized license plates, exhaust modifications, and dangerous stunts like wheelies in real time. Deep learning and computer vision techniques are used for video and audio analysis. The system automates violation detection, reducing human effort and enhancing traffic rule enforcement

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

HSRP detection, Number plate recognition, vehicle violation detection ,image processing.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A surveillance camera is an essential security device used for monitoring and recording activities in a specific area. It is commonly used in various settings such as homes, businesses, public spaces, and industrial sites to deter crime, monitor behavior and ensure safety. Surveillance cameras are typically connected to a system for remote viewing and recording, allowing users to observe live footage or review past events. AI-powered surveillance cameras represent a significant advancement in security technology, integrating artificial intelligence and machine learning algorithms to provide more intelligent, automated, and accurate surveillance. Unlike traditional surveillance cameras that simply capture and record footage, AI-powered cameras have the ability to analyze data in real-time, recognize patterns, and make decisions based on predefined criteria. This leads to enhanced security, greater efficiency, and faster response times. AI-powered cameras can automatically identify and track objects or people within their field of view. Using machine learning and computer vision algorithms, these cameras can differentiate between humans, vehicles, animals, and other objects. They can also detect specific behaviors or events such as Intrusion detection, Loitering detection etc.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Surveillance camera, Fire detection, scream detection, Arduino, Emergency services, smart security, IOT based , smart surveillance system.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Workers monitoring and safety assurance bot in oil refinery using esp32 CAM introduces an intelligent surveillance and safety monitoring system using a mobile robot built on ESP32 architecture. It features real-time face recognition, environmental monitoring, and emergency response capabilities, controlled via a mobile application with automated alert systems. Designed to enhance workplace safety, particularly in hazardous environments like oil refineries, the system detects hazardous gases, temperature fluctuations, and motion anomalies, providing live video feeds and alerts to a central hub. Leveraging low-cost IoT technology, it aims to reduce workplace accidents, improve incident response times, and ensure compliance with safety regulations, making it a scalable and adaptable solution for industrial safety.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Workers Monitoring, Safety Assurance, ESP32-CAM, IoT-Based Surveillance, Face Recognition, Environmental Monitoring, Industrial Safety, Real-Time Alerts, Wireless Communication, Hazard Detection, Remote Monitoring, Autonomous Surveillance Bot.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project aims to develop a heliotropic system that enhance the performance of panels. It achieves this by using Light Dependent Resistor (LDR) sensors to detect sunlight intensity. Since the orientation of panels significantly impacts the amount of energy they collect, this system incorporates four LDR sensors positioned in different directions--North, South, East, and West. These sensors monitors sunlight levels from various angles, ensuring optimal positioning for greater energy absorption. The goal here is to design a heliotropic tracker that improves the panels performance using light sensors called Light Dependent Resistors (LDRs). It's well-known that light travels in straight lines from its source. In solar power systems, the alignment of solar panels with the setting sun is vital for maximizing energy capture. To achieve this, the project uses four LDR sensors arranged in a cross configuration, each facing North, South, East, and West. This is accomplished with the help of three servo motors that allow the solar panels to rotate. These motors control the horizontal (East-West) and vertical (North-South) movements, as well as the tilt of the system panels in relation to the sun's position. An Arduino microcontroller will manage the servo motors, directing the movement of the system panels based on the data received from the LDR sensors.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Component Solar Tracking System, Arduino Nano, Light Dependent Resistors (LDRs), Servo Motors, Solar Panel Orientation, Maximum Energy Absorption, Sunlight Intensity Detection, Buck Converter, Power Regulation, Automatic Sun Tracking, Real-Time Panel Adjustment, Renewable Energy Optimization, Dual-Axis Tracking, Efficiency Enhancement, Smart Solar Technology.

  License

Creative Commons Attribution 4.0 and The Open Definition