Department of Computer Science and Engineering, ABES Institute of Technology, Ghaziabad, U.P., India.
Department of Mathematics, College of Natural and Applied Sciences, University of Dar es Salaam, Dar es Salaam, Tanzania.
Comput Intell Neurosci. 2021 Aug 26;2021:5942574. doi: 10.1155/2021/5942574. eCollection 2021.
A rapid rise in inhabitants across the globe has led to the inadmissible management of waste in various countries, giving rise to various health issues and environmental pollution. The waste-collecting trucks collect waste just once or twice in seven days. Due to improper waste collection practices, the waste in the dustbin is spread on the streets. Thus, to defeat this situation, an efficient solution for smart and effective waste management using machine learning (ML) and the Internet of Things (IoT) is proposed in this paper. In the proposed solution, the authors have used an Arduino UNO microcontroller, ultrasonic sensor, and moisture sensor. Using image processing, one can measure the waste index of a particular dumping ground. A hardware prototype is also developed for the proposed framework. Thus, the presented solution for the efficient management of waste accomplishes the aim of establishing clean and pollution-free cities.
全球人口的迅速增长导致各国对垃圾的管理不善,引发了各种健康问题和环境污染。垃圾收集车每周只收集一到两次垃圾。由于垃圾收集方式不当,垃圾桶里的垃圾被扔到了街上。因此,为了应对这种情况,本文提出了一种使用机器学习(ML)和物联网(IoT)进行智能有效废物管理的高效解决方案。在提出的解决方案中,作者使用了 Arduino UNO 微控制器、超声波传感器和湿度传感器。通过图像处理,可以测量特定倾倒场的废物指数。还为提出的框架开发了硬件原型。因此,所提出的高效废物管理解决方案实现了建立清洁无污染城市的目标。