Title:Intelligent Waste Bin Monitoring with IoT Integration


Authors:Ayush Agrawal, Bhavik Joshi, Manoj Agrawal, Radheshyam Acholia


Published in: Volume 3 Issue 1 Jan June 2026, Page No.262-275


Keywords:Unmanned Aerial Vehicles (UAVs), Autonomous Cleaning Drone (ACD), Fac¸ade Clean ing, GPS-Denied Navigation, Digital Twin, SLAM


Abstract:These days, new technologies are helping to make life easier for people. Robots and drones are being used more and more. Because of the growing number of people, high-rise buildings are the way of the present and the future. The primary concerns, in addition to the safety concerns, are the cleanliness of these highrise buildings. The conventional mainte nance of high-altitude building fac¸ades is a paradigm defined by high operational costs, significant safety risks to human workers [1], and logistical complexity. While the deployment of Unmanned Aerial Vehicles (UAVs) has emerged as a promising alternative, this paper argues that current com- mercial systems are fundamentally constrained by a series of architectural and technological tradeoffs that limit their efficacy and scalability [2]. The existing market is bifurcated into two suboptimal architectures: tethered systems that offer unlimited endurance but suffer from con strained manoeuvrability and significant snag risks [3], and untethered battery-powered systems that pro vide high mobility at the cost of severely limited flight endurance and payload capacity [4]. Critically, both architectures exhibit a profound lack of autonomy, relying on manually operated, pilot-in-the-loop control systems that are fundamentally unsuited for the GPS denied ”urban canyon” environments where they are most needed [5]. This research paper addresses these deficiencies by proposing a novel framework for a next-generation Autonomous Cleaning Drone (ACD). The proposed system architecture is built upon three core innovations designed to overcome the identified limitations. The proposed framework represents a paradigm shift from remotely operated tools to a su-pervised autonomous system. This paper will demon strate, through architectural analysis and simulation, that this approach can significantly enhance safety and operational efficiency, while simultaneously unlocking new data-driven services such as automated fac¸ade inspection and building health monitoring.


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