IoT-Based Solid Waste Management Solutions: A Survey

Abstract

With the increase of population density and the rural exodus to cities, urbanization is assuming extreme proportions and presents a tremendous urban problem related to waste generation. The increase of waste generation has been considered a significant challenge to large urban centers worldwide and represents a critical issue for countries with accelerated population growth in cities. The Internet of Things (IoT) and cloud computing offer an automation possibility through cyberphysical systems that will change the way solid waste management is performed. Considering IoT requirements, a review analysis of waste management models available in the literature is performed in detail in this paper. Then, a deep review is undertaken of the related literature based on IoT infrastructure for efficient handling of waste generated in urban scenarios, focusing on the interaction among concessionaires and waste generators (citizens) from the perspective of a shorter collection time with reduced costs, as well as citizenship promotion. An IoT-based reference model is described, and a comparison analysis of the available solutions is presented, with the goal to highlight the most relevant approaches and identify open research issues on the topic.

Waste Management System Using IoT-Based Machine Learning in University

“…However, the idea has still some ambiguous problems in the system. To improve waste management, platform software for smart cities has been introduced in [14]; however, they only concentrated on the collection of data, and their platforms were comprised of technologies from other companies.…”

“…One important application is that IoT technology has become a practical and efficient tool to build smart cities. According to [14], a critical issue for a smart city is the increase of waste generation with accelerated population growth in cities. Two significant challenges for waste management are waste collection and path collection.…”

“…First, waste collection is a daily task in urban areas entailing the planning of waste truck routes, in which environmental, economic, and social factors must be considered. Second, the path length should be shortened, in order to avoid high fuel costs and reduce the work amount, by applying graph theory [14][15][16][17]. Some solutions have introduced the use of IoT devices to estimate the fill level of inboxes and send this data over the Internet to a server for decision-making [18][19][20][21][22][23].…”

Heterogeneous Sensing Data Analysis for Commercial Waste Collection

“…However, it is already highlighted that these technologies suffer from several issues (e.g., accuracy, sensor integration, and battery lifetime). As a result, this study aims to remedy these limitations by using ultrasonic filling detection sensors [12]. Table 2 displays a comprehensive analysis, conducted on the prior art on sensor-based waste collection, which was discussed in this literature.…”

An Integrated Turning Movements Estimation to Petri Net Based Road Traffic Modeling

“…According to the same study, the number of hours wasted annually across those studied economies is predicted to result in a 6% increase in the average during the period 2013-2030; therefore, drivers are expected to waste an additional 6.8 hours in gridlock each year. Smart cities can play a key role in facing the urbanization pressures and their associated issues [3][4][5] where information and communication technologies (ICTs) can be used while balancing the needs of present and future generations with respect to economic, social, and environmental aspects.…”