International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 09 | Sep 2024
p-ISSN: 2395-0072
www.irjet.net
EnviRoBot: An Innovative AI-Driven Waste Management System Using Unmanned Ground Vehicles (UGVs) Stachys Thangapapa A E1, Kogula Nandhitha K2, Rathnamala S3, Vijayashanthi T4 1 2Student, 3Associate Professor, 4Assistant Professor,
Dept. of Artificial Intelligence and Data Science, SIT, Kariapatti, Virudhunagar, Tamil Nadu, India ---------------------------------------------------------------------***--------------------------------------------------------------------1.2 Objectives Abstract - EnviRoBot is an advanced waste management system designed to address urban waste collection, sorting, and disposal challenges using Unmanned Ground Vehicles (UGVs) integrated with AI and IoT technologies. This paper presents the system's architecture, methodologies, and impact on sustainable urban waste management. Key features include real-time waste detection, automated sorting using AI algorithms, and route optimization with IoT sensors. EnviRoBot is solar-powered, promoting energy efficiency and sustainability. The prototype, built using the Firebird V ATmega2560 board, demonstrates the system's feasibility in real-world conditions, showcasing the potential of AI and IoT in revolutionizing waste management, contributing to cleaner and smarter cities.
The primary objective of EnviRoBot is to develop an autonomous waste management system using Unmanned Ground Vehicles (UGVs) integrated with AI and IoT technologies. This system aims to revolutionize urban waste collection and sorting by automating the entire process, from detection to disposal. EnviRoBot seeks to enhance operational efficiency through real-time monitoring and decision-making, optimize route planning to reduce energy consumption, and utilize AI algorithms for intelligent waste sorting. A key focus is on sustainability, achieved by powering the UGVs with solar panels, thus minimizing the environmental impact. Additionally, predictive maintenance capabilities are integrated to ensure minimal downtime, while the system's data-driven approach aids in policy-making and community engagement, ultimately contributing to smarter, cleaner urban environments.
Key Words:
Waste Management, AI, IoT, Unmanned Ground Vehicles (UGVs), Smart Cities, Firebird V ATmega2560, Predictive Maintenance, Sustainability.
1.INTRODUCTION
2. METHODOLOGY
Urban waste management is a growing challenge as cities expand. Traditional methods are often inefficient, costly, and environmentally unfriendly. This paper introduces EnviRoBot, an AI-driven waste management system that leverages Unmanned Ground Vehicles (UGVs) integrated with IoT technologies to automate waste collection, sorting, and disposal. The system is proposed to enhance operational efficiency, reduce human intervention, and promote sustainable waste management practices.
The EnviRoBot system is built around UGVs equipped with AI and IoT capabilities. The prototype, developed using the Firebird V ATmega2560 board, serves as the initial model to test and validate the system's core functionalities. The methodology involves waste detection, sorting, and collection processes, supported by advanced technologies for optimal performance.
2.1 System Design
1.1 Background
The UGVs, starting with the Firebird V ATmega2560 prototype, are fitted with sensors for waste detection and identification. AI algorithms are employed for sorting waste into categories, enabling efficient disposal or recycling. IoT sensors monitor the environment and optimize the UGVs’ routes, ensuring timely and effective waste collection.
The increasing volume of urban waste necessitates innovative solutions to ensure effective management. Existing systems struggle with inefficiencies in waste sorting, high operational costs, and limited real-time monitoring. The proposed Firebird V ATmega2560-based prototype of EnviRoBot addresses these issues by integrating AI algorithms for smart sorting and IoT sensors for route optimization, making waste management ecofriendly and more efficient.
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