International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 03 | Mar 2024
p-ISSN: 2395-0072
www.irjet.net
ECO EVOLVE: WASTE MANAGEMENT FLUTTER APPLICATION Achyut Raghuvanshi1, Abhishek Singh2, Dr. Ashish Baiswar3, Er. Priyanka4 1UG student of the Department of Information Technology, Shri Ramswaroop Memorial College of Engineering and
Management Lucknow, Uttar Pradesh, India
2UG student of the Department of Information Technology, Shri Ramswaroop Memorial College of Engineering and
Management Lucknow, Uttar Pradesh, India
3Associate Professor, Department of Information Technology, Shri Ramswaroop Memorial College of Engineering
and Management Lucknow, Uttar Pradesh, India
4Associate Professor, Department of Information Technology, Shri Ramswaroop Memorial College of Engineering
and Management Lucknow, Uttar Pradesh, India --------------------------------------------------------------***---------------------------------------------------------------
Abstract - This project aims to develop a waste
system incorporating deep learning and Internet of Things technologies for waste segregation purposes highlighting how advanced algorithms become an integral part of the waste classification process.
classification app using various techniques with an innovative Flutter app. The application will enable the users to register their complaints, look for the status of their complaints anytime, refer to the study resources, integrate Google Maps which can be used to locate recycling and disposal centres, and the user profiles. This system consists of different actors like users, admins, and government people. The app helps to advance waste classification with image recognition and user location data from Google ML Kit. A previous research project on this topic used CNN architectures for image classification in the waste classification process. Furthermore, sensorbased technologies also contribute to the efficiency of waste sorting systems. The project aims to support environmental conservation by offering waste management as an ecological service. This is achieved through the integration of advanced technology.
Also, the use of Google Machine Learning kit in waste management applications has gained attention over time for its effectiveness in improving the classification accuracy of wastes and the speed of the entire process. Analogous to Aarif et al. (2022), various deep learning algorithms have proved their proficiency and determined how artificial intelligence can make the sustainability of waste management practices possible. Moreover, Khatun et al. (2022) demonstrated an AI-enabled IoT system for route recommendations from a smart waste management point of view, suggesting the use of such methods in routing optimization and resource allocation. The joining of IoT, devices that are used to measure things, Flutter applications, and Google ML Kit in waste management systems gives an occurrence that has to do with being innovative so that environmental problems can be resolved, the use of sustainable practices can be promoted and the waste management processes optimized. In this paper, through the integration and the further development of the currently existing research in waste management, we intend to dot the i’s and cross the t’s of the already existing waste management technologies and methods, with a particular focus on the incorporation of the latest technologies designed for advanced waste segregation and classification.
Key Words: Waste Management, GPS Tracking, Garbage Disposal, Flutter, Mobile Application, Google ML Kit, Firebase
1. INTRODUCTION Waste management is a pressing issue worldwide, hence the introduction of advanced solutions and systems to solve segregation, categorization, and dumping issues. The application of the Internet of Things (IoT), sensors, Flutter applications, and Google ML Kit seems to be the latest development in waste management strategies. The latest research has shown the capability of IoT-based solutions in remaking waste management systems. Studies like Shukla & Shukla (2017) have carried out surveys of Smart Waste Collection Systems based on IoT where the potential of IoT in enhancing collection efficiency and sustainability is stressed. Moreover, Dandge (2023) investigated the development of a Flutter-based Android platform for Smart Waste Management Systems which featured the user-friendly and integrated solutions provided by modern technologies for waste disposal optimization. On the other hand, Aarif et al. (2022) proposed a Smart Bin
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2. SCOPE User Task: The given references point out that the goal of this step is to distinguish and select appropriate scientific methodologies and techniques that can be applied in the design of the waste classification mobile application with the help of Flutter. The employed techniques should encompass waste management methods, proper classification systems, recycling processes, and all green approaches. The aim is to exploit the successful research approaches that will help in the
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