International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 04 | Apr 2024
p-ISSN: 2395-0072
www.irjet.net
Autonomous Water Guardian (AWG) for Water Waste Management Prof. Rupali Dupade1, Kunal Kulkarni2, Shivam Bhagne3, Prathamesh Adinawar4, Maiz Sunjufy 5 1 Assistant Professor, Department of Computer Engineering 2,3,4,5 Students, Department of Computer Engineering
Jayawantrao Sawant College of Engineering, Pune, India. ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Water pollution, a pressing global issue,
A groundbreaking solution empowered by advanced technologies such as machine learning (ML), Internet of Things (IoT), and cloud computing.
threatens the sustainability of aquatic ecosystems and human health. Conventional waste management approaches often struggle to address the magnitude of this challenge effectively. To tackle this problem, we propose an innovative solution: the Autonomous Water Guardian (AWG). Leveraging machine learning (ML) and Internet of Things (IoT) technologies, the Autonomous Water Guardian functions as an autonomous boat cleaner, tasked with navigating water bodies and autonomously collecting waste. The Autonomous Water Guardian integrates a suite of sensors to monitor water quality continuously. These sensors provide real-time data, which is transmitted to a cloud server for analysis and storage. Upon detecting contamination, the AWG initiates a cleaning process to restore water quality. Waste collected during cleaning operations is managed in onboard tanks, and notifications are dispatched when these tanks approach full capacity. Key features of the Autonomous Water Guardian (AWG) include its ability to autonomously collects and manages waste, data transmission to municipal authorities is carried out manually, this facilitates rapid response to significant changes in water quality. By automating waste collection and management, the AWG enhances operational efficiency and safety, mitigating the risks associated with manual labor and hazardous waste handling. This interdisciplinary project underscores the synergy between machine learning (ML), IoT technologies and cloud computing in addressing complex environmental challenges. By providing a sustainable solution to water pollution and waste accumulation, the AWG contributes to the preservation of aquatic ecosystems, public health, and resource conservation
The Autonomous Water Guardian represents a paradigm shift in water waste management, offering a comprehensive and efficient approach to monitoring and cleaning water bodies. At the core of the AWG's functionality are a myriad of sensors, including the HX711 and 5kg load cell for precise weighing of waste collected, DHT11 sensor for humidity monitoring, and a pH sensor for real-time water quality assessment. These sensors work in tandem to provide accurate and timely data on water conditions, enabling proactive intervention to prevent contamination and safeguard water resources. Central to the AWG's operation is its integration with a cloud platform, leveraging the Blynk IoT platform for seamless data transmission and management. Through the Blynk mobile application, users have access to real-time information on water quality, waste levels, and operational status of the AWG. Furthermore, the AWG's intelligent notification system alerts users when the waste bin reaches full capacity, triggering automated collection processes. A key innovation of the AWG is its waste collection mechanism, facilitated by an elevator-like structure designed to efficiently retrieve and store waste. Equipped with a camera for object detection, the AWG utilizes the YOLO v7 algorithm to identify and classify waste materials, ensuring targeted and effective cleaning operations. Additionally, GPS technology, integrated through the Neo6M module, enables precise navigation of the AWG, ensuring optimal coverage of designated water bodies
Key Words: Water pollution, IoT, Autonomous Water Guardian (AWG), Cloud Computing, Waste Management, Environmental Sustainability, Machine Learning, IOT Technologies, Interdisciplinary Solutions
Powered by a Raspberry Pi 4 Model B 4GB, the AWG operates autonomously, following predefined routes and efficiently collecting waste up to 5kg in weight. Through meticulous programming and hardware integration, the AWG embodies the convergence of cutting-edge technologies to address pressing environmental challenges
1.INTRODUCTION Water pollution poses a significant threat to the sustainability of aquatic ecosystems and human health worldwide. Despite efforts to mitigate this issue, traditional waste management methods often fall short in addressing the complex challenges associated with water contamination and waste accumulation. To address these challenges, we introduce the Autonomous Water Guardian (AWG),
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Impact Factor value: 8.226
In this paper, we present a comprehensive overview of the design, implementation, and performance evaluation of the AWG. We highlight its innovative features, including sensor integration, cloud connectivity, waste detection, and autonomous navigation. Furthermore, we discuss the
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