A review of IoT-based smart waste level monitoring system for smart cities

Shah, Ashfaque Ahmad; Fauzi, Shukor Sanim Mohd; Gining, Ray Adderley Jm; Razak, Tajul Rosli; Jamaluddin, Muhammad Nabil Fikri; Maskat, Ruhaila

doi:10.11591/ijeecs.v21.i1.pp450-456

Cited by 14 publications

(6 citation statements)

References 41 publications

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“…SW management systems within a smart city framework. In literature, automation models are proposed for the classification of SW, finding an element in common corresponding to the intention of developing integral management systems [22], [29], [30]. Application design tailored to user psychology.…”

Section: Trendsmentioning

confidence: 99%

Review on techniques of automatic solid waste separation in domestic applications

et al. 2022

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The accelerated modern day urban development is accompanied by an increasing production of solid waste. While managing solid waste on an industrial scale presents different technological challenges, managing household waste requires decentralized solutions dealing with the associated logistic and technical difficulties. In this review, we identify the research trends on household waste recycling by providing a brief description of the main technologies, and the traditional formats commonly used for solid waste (SW) separation. We identify two main threads: the SW management systems within a smart city framework and the design of domestic waste classification systems based on intelligent mechanisms tailored to user psychology. Among the main conclusions, we verify a growing interest in the subject of SW separation in domestic applications, mainly through solutions based on automation and internet of things (IoT). Also, we detected a increasing interest in the analysis of psychological aspects and in citizen education in relation to the importance of recycling, since without this notion the success of proposed solutions might be limited.

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Section: Trendsmentioning

confidence: 99%

Review on techniques of automatic solid waste separation in domestic applications

et al. 2022

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“…Users requesting sensor's current value, stopping data recovery, and setting the time interval, among other things [22]. As a result, the Arduino can send data to the IoT application via Wi-Fi or other communication protocols, which can create a dedicated channel and contain counters to measure and store data for specific time periods [23]. Thing speak has been used to store and retrieve data from SGI devices as an IoT application.…”

Section: Communication Protocolmentioning

confidence: 99%

Smart internet of things kindergarten garbage observation system using Arduino uno

Aldujaili

Dauwed

Meri³

et al. 2022

IJECE

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<span lang="EN-US">Increase the in population and kindergarten number, especially in urban areas made it difficult to properly manage waste. Thus, this paper proposed a system dedicated to kindergartens to manage to dispose of waste, the system can be called smart garbage based on internet of things (SGI). To ensure a healthy environment and an intelligent waste in the kindergarten management system in an integrated manner and supported by the internet of things (IoT), we presented it in detail identification, the SGI system includes details like a display system, an automatic lid system, and a communication system. This system supplied capabilities to monitor the status of waste continuously and on IoT website can show the percentage of waste placed inside the bin. And by using a Wi-Fi communication system, between the system unit and the monitoring body, to collect waste when the trash is full. The smart system proposed in this paper is the most efficient system of traditional waste management systems because it reduces the use of manpower and significantly limits the spread of waste and fully controls it. Additionally, it can be linked via the IoT to the mobile, thus forming an integrated monitoring system.</span>

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“…The analysis of data that is gathered will help the government to improve their plans. The system also helps generate reports for the smart waste management [16].…”

Section: Key Findingsmentioning

confidence: 99%

IoT based Smart Waste Management Using Deep Reinforcement Learning

Rajani¹,

Gaddam²,

Gaddam³

2022

Preprint

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Ever-increasing need for improving the livability of a city and improve outcomes for its residents, over the last decade, the adoption of technology to develop urbanised societies around the world has given rise to the need for developing smart cities. The speed at which the world population is growing, the use of Internet of Things in smart cities have really advanced the quality of life. One significant area of concern within the smart city framework is waste management. If the waste within a city is not adequately managed, then it leads to issues in the health of the citizens. Additionally, the waste management has such a high impact on the environmental footprint, hence the need to have a smart way of managing waste is of critical importance. Through our research, we analyse the challenges of waste management within a city to understand the impact of the problem on to the citizens and overall city operations. We then investigate ways in which we can solve these problems using the emerging technologies, such as the Internet of Things, to collect valuable data of large volumes arriving at an astronomical rate, then apply multi-agent deep reinforcement learning algorithms to harness the power of big data to extract meaningful information and actionable insights. We ingest data generated by our Internet of Things into our algorithm for three main purposes including providing the notifications to an external system, for example, a map navigation engine out of the scope for this project but a future extension for route optimisation and waste vehicle tracking; extracting and reporting the actionable insights from the underlying data; and consuming the extracted data for predictive forecasting to draw out the unknown patterns of waste fill levels within various geographical locations and again send out triggers and notification to external systems for example a waste collection authority who can efficiently schedule the waste collection vehicles and optimise the route. To achieve the above mentioned outcomes, we propose a framework that is agnostic of the hardware that it connects to and can effectively interface with a wide variety of hardware keeping a level of abstraction in the architecture.

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A review of IoT-based smart waste level monitoring system for smart cities

Cited by 14 publications

References 41 publications

Review on techniques of automatic solid waste separation in domestic applications

Review on techniques of automatic solid waste separation in domestic applications

Smart internet of things kindergarten garbage observation system using Arduino uno

IoT based Smart Waste Management Using Deep Reinforcement Learning

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