International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 04 | Apr 2025
p-ISSN: 2395-0072
www.irjet.net
AI-Enabled Smart Bin For Waste Management And Rainwater Detection With Real-Time Monitoring Sanskruti More1, Akanksha Bhosale2, Krutika Bhide3, Khushi Beluse4, Dr. Nita Patil5 1,2,3,4- Student, Department of Computer Engineering, K. C. College of Engineering, Thane, India 5 – Prof. Department of Computer Engineering, K. C. College of Engineering, Thane, India
---------------------------------------------------------------------***--------------------------------------------------------------------help prevent overflow, odor problems, and inefficient Abstract - Current urban waste management practices waste collection.
are contributing to significant operational inefficiencies, including unnecessary fuel consumption, increased travel time, and elevated environmental impact due to ineffective collection methods. Overflowing bins, missed pickups, and the frequent servicing of underfilled containers highlight the shortcomings of traditional systems. These challenges not only strain municipal resources but also lead to higher carbon emissions and reduced service quality. To address these issues, this paper focuses on an advanced solution that integrates Internet of Things (IoT) technology into urban waste management. The system employs smart sensors and automated data collection to remotely monitor bin fill levels in real time, improving the efficiency of waste collection operations. By continuously gathering bin status data, the system enables route optimization, cutting fuel usage by 25% and minimizing travel time, which enhances operational efficiency and reduces environmental impact. The system analyzes historical data to identify patterns in waste generation, such as peak disposal periods and highwaste areas. This insight supports predictive planning, allowing waste management teams to allocate resources effectively and schedule collections based on actual needs. As a result, resource utilization is improved, while bin overflows and unnecessary collection trips are significantly reduced, promoting a more sustainable and efficient waste management process.
The integration of IoT-based solutions helps optimize waste collection schedules by reducing unnecessary trips, which in turn lowers fuel consumption and greenhouse gas emissions. Additionally, the implementation of wireless communication modules, such as NodeMCU, allows seamless data transfer for real-time monitoring and decision-making. Such data-driven insights assist authorities in managing waste more effectively by identifying trends and optimizing collection routes. Further advancements, including liquid waste sensors, expand the capabilities of smart waste management systems by addressing both solid and liquid waste challenges. These innovations enhance urban cleanliness, improve public health conditions, and ensure a more efficient and adaptive waste management infrastructure. The following sections will provide a detailed literature survey analyzing prior research on IoT-based waste management systems, their advantages and disadvantages. Furthermore, the paper will cover the methodology used for implementing smart waste management, present a conclusion, and discuss the future scope for improving waste management systems through emerging technologies.
2.LITERATURE SURVEY
Key Words: IoT, Sensors, Arduino, Smart Wastage Monitoring, AI, Optimization
K. Mehta and L. Verma (2024) introduced an AI-driven smart waste management system utilizing IoT and machine learning. IoT sensors placed in bins monitor waste levels and send real-time data, while cloud data processing is used to store and analyze waste accumulation patterns for improved management. [1]
1.INTRODUCTION Waste management plays a vital role in ensuring hygiene and environmental sustainability. However, conventional waste disposal methods often encounter issues such as overflowing bins, inefficient collection processes, and delayed pickups. These challenges contribute to environmental hazards, health risks, and increased strain on municipal resources. To mitigate these issues, advancements in technology, particularly the Internet of Things (IoT), have been introduced to enhance waste management efficiency [2]. By incorporating IoT, microcontrollers such as Arduino, and sensor technologies, real-time waste monitoring has become feasible. Smart waste bins equipped with ultrasonic and liquid sensors can detect waste accumulation levels and
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G. Uganya, D. Rajalakshmi, Y. Teekaraman, R. Kuppusamy, and A. Radhakrishnan (2023) developed an IoT-based intelligent waste management system. The system uses IoT sensors to collect real-time waste data and applies machine learning algorithms to predict waste trends, enabling better planning and resource allocation. [2] H. Patel and V. Desai (2023) worked on sustainable waste management through IoT and cloud integration. IoT sensors detect waste levels and transmit data to the cloud,
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