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An intelligent framework of route optimization to garbage collector vehicle in hilly city Shimla, India

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Abstract

The rapid growth of population, urbanization, and tourist traffic in Shimla City, Himachal Pradesh, has resulted in a continuous rise in municipal solid waste (MSW) generation every year. The Internet of Things (IoT) initiatives in smart cities led to efficient waste management for a clean and green ecosystem. The goal of this research is to find a novel route planning approach for Shimla City by reducing environmental and socioeconomic impacts. In this paper, reallocating collection bins improves collection efficiency, and the Temporal-Neural Network (T-NN) is used to control the overflow and predict the optimal route for collection vehicles in the city. Over the spatio-temporal patterns, various events are related in the form of time series snips at different periods. A classifier, fuzzy C-means (FCM), is used to classify a route based on several hilly city features. Following that, the optimal index for each potential route is determined, and the path with the lowest ROI value is chosen as the best route. Based on the simulation, the results show that the proposed approach outperforms other state-of-the-art techniques in terms of the lowest fuel consumption, cost (10.7%), and execution time (12.3%). Furthermore, statistical measures such as recall (96.8%), accuracy (95.9%), F-measure (93.87%), and precision (95.6%) show that the proposed approach also outperforms the other techniques.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Lovely Professional University, Phagwara, Punjab, India

    Meenakshi Shruti Pal

  2. Department of Computer Applications, NIT Kurukshetra, Kurukshetra, India

    Munish Bhatia

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  1. Meenakshi Shruti Pal
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Correspondence to Munish Bhatia.

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Responsible Editor: Amjad Kallel.

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Pal, M.S., Bhatia, M. An intelligent framework of route optimization to garbage collector vehicle in hilly city Shimla, India. Arab J Geosci 15, 1677 (2022). https://doi.org/10.1007/s12517-022-10957-y

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