Smart Prediction and Monitoring of Waste Disposal System Using IoT and Cloud for IoT Based Smart Cities

被引:28
作者
John, Jacob [1 ]
Varkey, Mariam Sunil [1 ]
Podder, Riya Sanjay [1 ]
Sensarma, Nilavrah [1 ]
Selvi, M. [1 ]
Santhosh Kumar, S. V. N. [2 ]
Kannan, Arputharaj [1 ]
机构
[1] Vellore Inst Technol, Sch Comp Sci & Engn, Vellore, Tamil Nadu, India
[2] Vellore Inst Technol, Sch Informat Technol & Engn, Vellore, Tamil Nadu, India
关键词
IoT; Smart cities; Waste management; LSTM; Recurrent neural network; Sensors; ALGORITHM; INTERNET;
D O I
10.1007/s11277-021-08897-z
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
One of the prominent applications of Internet of Things (IoT) in this digital era is the development of smart cities. In IoT based smart cities, the smart objects (devices) are connected with each other via internet as a backbone. The sensed data by the smart objects are transmitted to the sink for further processing using multi hop communication. The smart cities use the analyzed data to improve their infrastructure, public utilities and they enhance their services by using the IoT technology for the betterment of livelihood of the common people. For IoT based smart cities, waste collection is a prominent issue for municipalities that aim to achieve a clean environment. With a boom in population in urban areas, an increasing amount of waste is generated. A major issue of waste management system is the poor process used in waste collection and segregation. Public bins begin to overflow for a long period before the process of cleaning starts, which is resulting in an accumulation of bacteria causing bad odors and spreading of diseases. In order to overcome this issue, in this paper an IoT based smart predication and monitoring of waste disposal system is proposed which utilizes off-the-shelf components that can be mounted to a bin of any size and measure fill levels. An Arduino microcontroller is employed in the proposed model to interface the infrared (IR), ultraviolet (UV), weight sensors, and a Global Positioning System (GPS) module is used to monitor the status of bins at predetermined intervals. The proposed system transmits the data using the cluster network to the master module which is connected to the backend via Wi-Fi. As data is collected, an intelligent neural network algorithm namely Long Short-Term Memory (LSTM) is used which will intelligently learn and predict the upcoming wastage from waste generation patterns. Moreover, the proposed system uses Firebase Cloud Messaging to notify the appropriate people when the bins were full and needed to be emptied. The Firebase Cloud Messaging (FCM) JavaScript Application Programming Interface (API) is used to send notification messages in web apps in browsers that provide service work support. Hence, the proposed system is useful to the society by providing facilities to the governments for enforcing stricter regulations for waste disposal. Additional features such as automated calibration of bin height, a dynamic web data dashboard as well as collation of data into a distributed real-time firebase database are also provided in the proposed system.
引用
收藏
页码:243 / 275
页数:33
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