Energy-Efficient Routing in Smart Parking Networks Using the Metaheuristic Approach

Authors

  • Aadya Singh School of Computer Engineering, KIIT (Deemed to Be) University, Bhubaneswar-751024, Odisha, India.
  • Ashi Rai * School of Computer Engineering, KIIT (Deemed to Be) University, Bhubaneswar-751024, Odisha, India.
  • Anushka Banerjee School of Computer Engineering, KIIT (Deemed to Be) University, Bhubaneswar-751024, Odisha, India.
  • Hitesh Mohapatra School of Computer Engineering, KIIT (Deemed to Be) University, Bhubaneswar-751024, Odisha, India. https://orcid.org/0000-0001-8100-4860

https://doi.org/10.48313/maa.v2i1.23

Abstract

At present, drivers face considerable challenges in finding parking spots due to traffic congestion in certain areas and the distribution of parking spaces across the city. The initiative aims to develop a cutting-edge system that allows vehicles to navigate to their current location while finding available parking in a designated area. Additionally, it suggests implementing energy-efficient strategies to mitigate environmental impact and reduce operational costs. In terms of emergency response, a concept is introduced that involves placing sensors in vehicles within a 200-meter radius. This would allow ambulances to quickly find unoccupied parking spaces, minimizing the number of pedestrians in busy areas and lowering fuel consumption, which ultimately saves both time and lives. By focusing on security, energy efficiency, and innovative approaches, Smart Parking solutions can significantly enhance the sustainability and functionality of urban settings. To achieve the objective of optimizing energy efficiency, the Amplified-ACO (A^2 CO) routing algorithm, based on Ant Colony Optimization (ACO) principles and utilizing the probabilistic selection model DS^2, which is determined by Distance, Speed, and State-of-Charge, is used to ensure the highest energy efficiency attainable.

Keywords:

IoT, Big data, LoRa networks employ energy-efficient routing in wireless sensor networks, Neural networks to enhance smart parking systems, Improving energy efficiency and reducing search times for available spaces

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Published

2025-03-14

Issue

Vol. 2 No. 1 (2025): Metaheuristic Algorithms with Applications (MAA)

Section

Articles

How to Cite

Singh, A. ., Rai, A. ., Banerjee, A. ., & Mohapatra, H. . (2025). Energy-Efficient Routing in Smart Parking Networks Using the Metaheuristic Approach. Metaheuristic Algorithms With Applications, 2(1), 36-47. https://doi.org/10.48313/maa.v2i1.23