Abstract
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.
Highlights
4.67 kilograms. e overall waste is anticipated to exceed about 45 billion tons by 2055, which will be over double growth for the identical period
E most effective solution to overcome the problem of environmental pollution is the use of the Internet of ings(IoT-) and machine learning- (ML-) based waste management system [5]. ese technologies can provide real-time information about the waste and provide an optimized path for the waste collection trucks, reducing the cost and time for the overall process. e issues faced by current waste management systems are improper scheduling; that is, the waste collectors do not know that they had to pick the waste
E smart waste management system can be administered and supervised using machine learning and the Internet of ings. e system proposed by the authors functions with the ultrasonic sensor and moisture sensor as shown in Figure 4. e ultrasonic sensor will depict the assorted distance from waste in the dustbins. is sensor ranges from 2 cm to 400 cm measurement function of noncontact. ese sensors are deployed on the dustbins, and they detect the level of waste in the dustbins. e Arduino UNO microcontroller further gives the indications
Summary
Waste management is an essential part of maintaining a city’s hygiene and health. Developed countries have adequate resources and equipment to sustain these favorable conditions, such as up-to-date and even real-time waste generation statistics, qualified personnel, and current fleets of collection trucks equipped with the most cutting-edge technical breakthroughs or instruments, such as geographical information systems. Most respondents agree that minimizing food waste necessitates a systematic approach involving a cyclical process of reducing, reusing, and recycling to reduce the problem caused by poor food handling; waste created during meal preparation is a concern in the home They largely agree with the advice that a mandatory food waste recycling system for private households is introduced immediately and closely monitored by authorities in order to tackle the pressing issue of food waste efficiently and effectively [27]. Collecting half of the MSW and recycling 15% of the plastic content will cover the expense of handling plastic-related waste; depending on the recovery rate, collection quality, and price of recovered plastic, the flow of financial resources can fluctuate Additional policy initiatives, such as the standardization of packaging materials and infrastructure construction, will aid in the better management of MSW in the long run [32]. If the waste index of a particular dumping ground is high, priority is given to that dumping ground. e authors have deployed sensors in the dustbins which will help to find the priority of one dustbin over the other
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