Patil Sangram Chandrakant
Biography
Assistant Professor
Department of Civil Engineering
Bharati Vidyapeeth's College of Engineering, Lavale, Pune.
A highly motivated and results-oriented Ph.D. candidate in “Smart Solid Waste Management for a Region” with 8.5 Years of experience as a college professor. Possesses a strong foundation in research, teaching, and curriculum development. Proven ability to engage students, foster critical thinking, and contribute to a vibrant academic community.
Research Interest
Civil Engineering, Smart Solid Waste Management for a Region
Abstract
Smart Solid Waste Management for a Region
Solid Waste Management (SWM) has become a pressing challenge for rapidly urbanizing regions, particularly in Indian smart cities. This research explores the complex issues surrounding SWM, driven by changing consumption patterns, unregulated urban expansion, and industrialization. Municipal solid waste comes from diverse sources, including households, commercial sectors, markets, slaughterhouses, institutions, horticulture, road sweeping, drainage silt, and biomedical waste. The rapid urbanization and population growth in Indian smart cities have compounded these challenges, leading to severe environmental and public health concerns.
This research proposes a comprehensive framework to address SWM challenges by incorporating strategies for waste reduction, segregation, collection, transportation, treatment, and disposal through the use of Internet of Things (IoT) and IT solutions. It integrates IoT technologies such as RFID for unique user identification, GPS for tracking waste collection locations, RFID readers for data transmission to central databases, and ultrasonic sensors to monitor waste levels in dustbins. Additionally, Management Information Systems (MIS) are employed to optimize waste collection routes and implement web and Android-based waste management solutions.
The primary study focuses on implementing IoT and IT solutions at the ward level, aiming to minimize waste and achieve 100% door-to-door waste collection, transportation, and processing. This includes eliminating open dumping at landfill sites and scientifically selecting appropriate landfill locations.
The study is structured around five key objectives to improve waste segregation, optimize collection routes, achieve complete waste processing, and minimize environmental impact. For the first objective, extensive data collection and statistical analysis were conducted on four waste types—dry, wet, bio, and e-waste—over two months (February and March 2023). Findings reveal a significant increase in waste collection, with dry waste rising from 11,466 tons in February to 22,354 tons in March. Strong correlations were observed between various waste types, particularly dry and wet waste, indicating consistent disposal patterns across households. The analysis, using distribution plots, correlation plots, and QQ plots, provides novel insights into waste generation patterns, including the identification of outliers in e-waste collection.
For the second objective, IoT technologies were applied through smart waste bins and a centralized waste management dashboard. Real-time tracking of waste collection allowed for better route optimization and improved efficiency. The integration of IoT and data analytics led to a linear increase in waste collection, highlighting the system’s scalability and effectiveness. This represents a significant advancement in urban waste management, offering a scalable solution for future implementations.
The third and fourth objectives focus on achieving 100% waste processing through improved recycling, composting, and reuse practices. Public awareness campaigns andsurveys revealed that over 80% of residents were willing to segregate waste for recycling, and more than 56% actively participated in composting at the household level. Additionally, 95% of residents expressed interest in responsibly disposing of e-waste. The novelty of this research lies in the combination of technological solutions with community engagement, driving higher public participation in sustainable waste management practices.
Finally, Geoinformatics and multi-criteria analysis were used to identify optimal solid waste disposal sites, minimizing reliance on open dumping. The suitability analysis identified nine potential sites, providing sustainable solutions for urban waste disposal.
A major focus of this research is on 100% waste processing with public participation. While previous studies primarily emphasized waste collection, this research extends further to achieve complete waste processing. It incorporates comprehensive strategies for recycling, composting, and reuse, complemented by public awareness campaigns. By engaging households directly, the study encourages broader adoption of sustainable practices such as e-waste disposal and composting—areas overlooked in earlier studies. Furthermore, this work integrates predictive analytics using tools like correlation plots, QQ plots, and distribution plots to offer deeper insights into waste generation patterns, marking a significant contribution to the field of waste management. Earlier research primarily focused on retrospective analysis, neglecting predictive analytics, which is a key innovation in this work.
Overall, this research introduces a comprehensive, smart waste management system that integrates IoT innovations, data analytics, and community involvement to improve urban waste collection, segregation, and processing. The findings demonstrate that the proposed system can significantly enhance efficiency, promote sustainability, and reduce environmental impact, representing a novel and substantial contribution to the field of waste management.
Keywords: Urbanisation, Solid Waste Collection, Swachh Bharat Abhiyan (Clean India Mission), Smart City development, RFID and IOT system, Integration of solid waste management.
