![]() Presently, 13 provinces in KSA involve the Northern Borders Region, Al-Jawf, Tabuk, Ha’il, Medina, Al-Qassim, Riyadh, Eastern, Mecca, Al-Bahah, ‘Asir, Jizan and Najran, as shown in Figure 1. Regions or provinces are the top-level executive unit in KSA. The median rate of waste generation is predicted to grow to 30 million tons by 2033 due to persistent population growth and urban widening. ![]() The KSA makes approximately fifteen million tons of municipal solid waste (MSW) every year, with a daily rate of 1.4 kg per individual. This increase comes as a result of the continuing widening of the holy mosques, improving safety and transportation services, and minimizing aggregate time and cost. In recent decades, the number of pilgrims visiting KSA for Hajj (the 12th month of the Islamic lunar calendar) has notably risen, with an annual increase of 1.15% from 1993 to 2014. ![]() These areas are the holy mosques al Haremeyn (Makkah and Medina) and Al-Masha’ir (Arafat, Mina and Muzdalifah). Holy areas of worship are visited by millions. The proposed system outperforms other systems by reducing the number of locations and smart bins that have to be visited by 46% for all waste types, whereas the conventional and existing systems have to visit all locations every day, resulting in high cost and consumption time.Īn enormous number of Muslims go to the Kingdom of Saudi Arabia (KSA) every year to perform Umrah and Pilgrimage (Hajj). The selected routes based on the volume status and free spaces of the smart bins are the most effective through those obtainable towards the urgent smart bin targets. A genetic-based optimization algorithm for waste collection transportation enhances the performance of waste-gathering truck management. Issues relating to the sustainability of organic waste management are conceptually analyzed. In this work, the situations in KSA are evaluated, and relevant aspects are explored. Each container is used for one type of waste, such as food, plastic and others, and uses the optimization algorithm to calculate and find the optimal route toward the full waste container. The open public area and the small space location problems are solved by proposing different truck sizes based on the waste type. Waste source locations and population density influence the volume of waste generation, especially waste food, as it has the highest amount of waste generation. The conventional system cannot observe a real-time update of the bin status to recognize whether the waste level condition is ‘full,’ ‘not full,’ or ‘empty.’ This paper uses IoT in the container and trucks that secure the overflow and separation of waste. It works based on a planned scheme that is implemented by the authorized organization focused on specific popular and formal areas. The conventional waste collection system does not cover all areas in the city. However, from another perspective, the population and residents’ attitudes directly affect the control of the waste management system. A waste-gathering approach based on supplying smart bins is introduced by using an IoT prototype embedded with sensors, which can read and convey bin volume data over the Internet. This paper demonstrates how the incorporation of the Internet of Things (IoT) with data access networks, geographic information systems and combinatorial optimization can contribute to enhancing cities’ administration systems. Organizations unanimously concentrate on sustainability issues with key features of general trends, particularly the combination of the 3Rs (reduce waste, reuse and recycle resources). Many of these have envisaged a chance to establish devoted municipal access networks to assist all kinds of city administration and preserve services needing data connectivity. Urban areas worldwide are in the race to become smarter, and the Kingdom of Saudi Arabia (KSA) is no exception.
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