Smart Waste Management System Using ESP32

Mulani Mumtaj RajuUG Student, Electronic & Telecommunication Engineering Department, Fabtech Technical Campus, Maharashtra, IndiaPawar Swapnali DilipUG Student, Electronic & Telecommunication Engineering Department, Fabtech Technical Campus, Maharashtra, IndiaSawant Sonali BandopantUG Student, Electronic & Telecommunication Engineering Department, Fabtech Technical Campus, Maharashtra, IndiaKadam Akanksha AnnasoUG Student, Electronic & Telecommunication Engineering Department, Fabtech Technical Campus, Maharashtra, IndiaAsst. Prof. R.K. PatoleProfessor, Electronic & Telecommunication Engineering Department, Fabtech Technical Campus, College of Engineering and Research Sangola, Dr. Babasaheb Ambedkar Technological University, Lonere, Maharashtra, India

Vol 8 No 4 (2024): Volume 8, Issue 4, April 2024 | Pages: 280-284

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 19-05-2024

doi Logo doi.org/10.47001/IRJIET/2024.804043

Abstract

The Smart Waste Management System (SWMS) is designed to revolutionize traditional waste management practices by integrating Internet of Things (IoT) technology, data analytics, and real-time monitoring capabilities. The system utilizes a network of sensors deployed in waste bins to collect data on fill levels, location, and other relevant parameters. This data is transmitted wirelessly to a central server for analysis using advanced algorithms to optimize waste collection routes, schedule maintenance, and detect anomalies. Through a user-friendly web or mobile interface, stakeholders can access real-time information, receive alerts, and monitor the status of waste bins remotely. SWMS aims to improve operational efficiency, reduce environmental impact, and enhance public health by minimizing waste overflow, optimizing resource allocation, and promoting sustainable waste management practices. This abstract provides an overview of the SWMS's functionality, highlighting its potential to revolutionize waste management practices and contribute to a cleaner, smarter, and more sustainable urban environment.

Keywords

Iot, sensors, monitoring, waste, location


Citation of this Article

          

Mulani Mumtaj Raju, Pawar Swapnali Dilip, Sawant Sonali Bandopant, Kadam Akanksha Annaso, Asst. Prof. R.K. Patole, “IoT-Based Non-Invasive Blood Glucose Monitoring System”, Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 8, Issue 4, pp 280-284, April 2024. Article DOI https://doi.org/10.47001/IRJIET/2024.804043

References
  1. Pingili, Dr & Shiny, Dr & B, Bhavana. (2024). Implementation of Waste Management System. International Journal of Recent Trends In Multidisciplinary Research. 21-25. 10.59256/ijrtmr.20240401004.
  2. Munandar, A & Arahman, N & Ramli, I. (2024). An environmentally conscious waste management system in an effort to create a sustainable city (study of waste management systems at Syiah Kuala University). IOP Conference Series: Earth and Environmental Science. 1302. 012075. 10.1088/1755-1315/1302/1/012075.
  3. Meghazi Bakhouch, Salsabil & Ayad, Soheyb & Terrissa, Labib Sadek. (2024). Smart Waste Management System Based on IoT. 10.1007/978-3-031-53824-7_29.
  4. Madonsela, Benett & Semenya, Khomotso & Shale, Karabo. (2024). A Review of Indigenous Knowledge Systems and Their Application in Sustainable Solid Waste Management. World. 5. 219-239. 10.3390/world5020012.
  5. Publication, Gjr. (2024). The Intelligent Waste Management System. 4. 140-144. 10.5281/zenodo.11050825.
  6. Singh, Abhijeet & Mishra, Ankit. (2024). SMART WASTE MANAGEMENT SYSTEM AND METHOD (201911029778).
  7. Sülük, Kemal & Coskun, Sezen & Budak, Havva. (2024). Importance of Waste Management in terms of Quality Management System in Food Industry: Fruit Juice Concentrate Facility.
  8. Srivastava, Shubham & Agarwal, Unnati & Sharma, Dr. (2024). IOT BASED SMART WASTE MANAGEMENT SYSTEM USING ARDUINO. 226-232. 10.55524/CSISTW.2024.12.1.40.
  9. Garba, Danladi & Bello, Mukhtar & Baballe, Muhammad. (2024). THE INTELLIGENT WASTE MANAGEMENT SYSTEM. 3. 37-42.
  10. Babu, Kishore. (2023). Online Waste Management System. International Journal for Research in Applied Science and Engineering Technology. 11. 998-1005. 10.22214/ijraset.2023.53663.