Development of an IoT-based waste monitoring and notification system for smart environmental management

Enggar Utari, Ika Rifqiawati, Wahyuni Martiningsih, Izzal Ihasani, Aditya Rahman, Bagus Dwicahyono

Abstract


Rapid urban population growth has intensified solid waste generation, while many existing waste management systems still rely on manual inspection and single-parameter monitoring, resulting in delayed responses and inefficient handling. Previous studies have primarily focused on isolated sensing or offline monitoring, highlighting the need for integrated, real-time, and user-oriented waste monitoring solutions. This study used RnD method, proposes a smart garbage level and information hub (SIGALIH), an IoT based waste monitoring and notification system designed to address these limitations. SIGALIH combines multi-parameter sensing, including waste level, temperature–humidity, gas concentration, and ambient light, with an ESP32 microcontroller, a cloud-based data platform, and a real-time notification service using a messaging bot. System evaluation involved sensor accuracy testing, communication latency analysis, and functional verification. Experimental results indicate an average sensor accuracy of 96.8%, with an average data transmission latency of 1.84 seconds and a notification delay of 2.14 seconds, indicating reliable real-time performance under varying network conditions. Functional testing confirmed stable operation of all system modules. The system was also integrated into an Environmental Education learning module to support environmental literacy and awareness through contextual learning on sustainable waste management. SIGALIH is designed for small- to medium-scale urban and community-based applications. However, performance depends on wireless network availability, which may reduce reliability in low-connectivity areas. Overall, SIGALIH provides a low-cost, scalable, integrated solution supporting smart environmental management and sustainable urban waste initiatives.

Keywords


Environmental monitoring; Internet of things applications; Real-time notification system; Smart city infrastructure; Wireless sensor network

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DOI: http://doi.org/10.11591/ijeecs.v42.i3.pp729-741

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES).

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