Forward Chaining Method Implementation for AI-Powered Passenger Ojek Online and Drive Solutions

Authors

  • Yamato Shino University of Miyazaki
  • Hani Ahsani Muhammadiyah Makassar University

DOI:

https://doi.org/10.34306/itsdi.v5i1.610

Keywords:

transportation, artificial intelligence, Forward Chaining

Abstract

This research explores the application of artificial intelligence (AI)-based technology in the Grab application, an online passenger transportation service company in Southeast Asia. The main aim of this research is to improve service quality, safety and efficiency for Grab passengers and drivers, while solving traffic and location problems. The use of AI in this application opens up opportunities to optimize passenger pick-up and drop-off processes, improve navigation, and improve real-time traffic management. Special emphasis is placed on the application of the Forward Chaining method, an artificial intelligence technique that allows systems to make decisions based on predetermined rules. By implementing this method, Grab can predict passenger movements and arrange the best routes automatically, increasing time efficiency and reducing congestion. The implications of this research are very significant in the context of improving the quality of online transportation services, by providing a better experience for passengers and ensuring safety on every trip. The main contribution of this research is the development of an efficient and reliable AI system, as well as the application of Forward Chaining in the context of the Grab application. Additionally, this research provides an in-depth understanding of how AI technology can overcome traffic and location challenges, creating effective and reliable solutions for ride-hailing companies in the future. The results of this research provide a valuable contribution to the development of transportation technology, providing a basis for similar companies to explore the potential of applying artificial intelligence in their services. Thus, this research paves the way to greater innovation in the field of online transportation, creating a more efficient, safe and comfortable environment for users, and creating significant added value for the industry.

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References

K. Guleria, S. Kumar, and A. K. Verma, “Energy Efficient Synchronous Media Access Control for Wireless Sensor Networks,” J Comput Theor Nanosci, vol. 17, no. 6, pp. 2523–2530, 2020.

H. Qiu, Q. Zheng, T. Zhang, M. Qiu, and ..., “Toward secure and efficient deep learning inference in dependable iot systems,” IEEE Internet of Things …, 2020, [Online]. Available: https://ieeexplore.ieee.org/abstract/document/9123371/

R. Regin, S. S. Rajest, and B. Singh, “Spatial Data Mining Methods Databases and Statistics Point of Views,” Innovations in Information and Communication Technology Series, pp. 103–109, 2021.

W. He, Z. J. Zhang, and W. Li, “Information technology solutions, challenges, and suggestions for tackling the COVID-19 pandemic,” Int J Inf Manage, 2021, [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0268401220314869

V. Hassija, V. Chamola, V. Gupta, S. Jain, and ..., “A survey on supply chain security: Application areas, security threats, and solution architectures,” IEEE Internet of …, 2020, [Online]. Available: https://ieeexplore.ieee.org/abstract/document/9203862/

T. C. King, N. Aggarwal, M. Taddeo, and L. Floridi, “Artificial intelligence crime: An interdisciplinary analysis of foreseeable threats and solutions,” Science and engineering …. Springer, 2020. doi: 10.1007/s11948-018-00081-0.

M. Yin, K. Li, and X. Cheng, “A review on artificial intelligence in high-speed rail,” Transportation Safety and Environment, 2020, [Online]. Available: https://academic.oup.com/tse/article-abstract/2/4/247/5891609

F.-Y. Wang et al., “Transportation 5.0: The DAO to safe, secure, and sustainable intelligent transportation systems,” IEEE Transactions on Intelligent Transportation Systems, 2023.

U. Rahardja, T. Hariguna, Q. Aini, and S. Santoso, “Understanding of behavioral intention use of mobile apps in transportation: An empirical study,” International Journal of Advanced Trends in Computer Science and Engineering, vol. 8, no. 1.5 Special Issue, pp. 258–263, 2019, doi: 10.30534/ijatcse/2019/4581.52019.

G. Allen, Understanding AI technology. apps.dtic.mil, 2020. [Online]. Available: https://apps.dtic.mil/sti/citations/AD1099286

J. Wanner, K. Heinrich, C. Janiesch, and P. Zschech, “How Much AI Do You Require? Decision Factors for Adopting AI Technology.,” ICIS. researchgate.net, 2020. [Online]. Available: https://www.researchgate.net/profile/Kai-Heinrich-3/publication/344350604_How_Much_AI_Do_You_Require_Decision_Factors_for_Adopting_AI_Technology/links/5f6b1b5d458515b7cf4701ea/How-Much-AI-Do-You-Require-Decision-Factors-for-Adopting-AI-Technology.pdf

R. Yunita, M. S. Shihab, D. Jonas, H. Haryani, and Y. A. Terah, “Analysis of The Effect of Servicescape and Service Quality on Customer Satisfaction at Post Shop Coffee Tofee in Bogor City,” Aptisi Transactions on Technopreneurship (ATT), vol. 4, no. 1, pp. 66–74, 2022.

Z. Zheng, A. Kind, and P. Chen, “Guest Editorial: Special Issue on Blockchain-Based Services Computing,” IEEE Trans Serv Comput, vol. 13, no. 2, pp. 200–202, 2020.

O. S. Al-Mushayt, “Automating E-government services with artificial intelligence,” IEEE Access, 2019, [Online]. Available: https://ieeexplore.ieee.org/abstract/document/8862835/

N. D. Dung, “Developing transport management system for integrating drones with smart cities.” Budapest University of Technology and Economics, 2021.

A. Nikitas, K. Michalakopoulou, E. T. Njoya, and ..., “Artificial intelligence, transport and the smart city: Definitions and dimensions of a new mobility era,” Sustainability, 2020, [Online]. Available: https://www.mdpi.com/680196

Y. Durachman, A. S. Bein, E. P. Harahap, T. Ramadhan, and F. P. Oganda, “Technological and Islamic environments: Selection from Literature Review Resources,” International Journal of Cyber and IT Service Management, vol. 1, no. 1, pp. 37–47, 2021.

A. J. T. Hardasmal and A. G. Salguero, “Teaching Parallelism With Gamification in Cellular Automaton Environments,” IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, vol. 15, no. 1, pp. 34–42, 2020.

P. Dhamija and S. Bag, “Role of artificial intelligence in operations environment: a review and bibliometric analysis,” The TQM Journal, 2020, doi: 10.1108/TQM-10-2019-0243.

A. M. Nascimento, L. F. Vismari, and ..., “A systematic literature review about the impact of artificial intelligence on autonomous vehicle safety,” … on Intelligent …, 2019, [Online]. Available: https://ieeexplore.ieee.org/abstract/document/8892611/

A. Asatiani, P. Malo, P. R. Nagbøl, E. Penttinen, and ..., “Challenges of explaining the behavior of black-box AI systems,” MIS Quarterly …, 2020, [Online]. Available: https://pure.itu.dk/da/publications/challenges-of-explaining-the-behavior-of-black-box-ai-systems

C. G. Walsh, B. Chaudhry, P. Dua, K. W. Goodman, and ..., “Stigma, biomarkers, and algorithmic bias: recommendations for precision behavioral health with artificial intelligence,” JAMIA …, 2020, [Online]. Available: https://academic.oup.com/jamiaopen/article-abstract/3/1/9/5714181

A. Khadija, F. F. Zahra, and A. Naceur, “AI-powered health chatbots: toward a general architecture,” Procedia Comput Sci, vol. 191, pp. 355–360, 2021.

F. Charles, “AI-Powered Personalized Mobile Education for New Zealand Students,” International Journal Software Engineering and Computer Science (IJSECS), vol. 3, no. 1, pp. 33–39, 2023.

M. Al Rajab, S. Odeh, S. Hazboun, and E. Alheeh, “AI-Powered Smart Book: Enhancing Arabic Education in Palestine with Augmented Reality,” in International Symposium on Ambient Intelligence, Springer, 2023, pp. 167–178.

A. Philip, C. S. Putri, and P. M. Arifanggi, “Traffic Light Timer Control Using Raspberry Pi,” Aptisi Transactions On Technopreneurship (ATT), vol. 1, no. 2, pp. 134–143, 2019.

D. Nallaperuma et al., “Online incremental machine learning platform for big data-driven smart traffic management,” IEEE Transactions on Intelligent Transportation Systems, vol. 20, no. 12, pp. 4679–4690, 2019.

P. Asha, L. Natrayan, B. T. Geetha, J. R. Beulah, and ..., “IoT enabled environmental toxicology for air pollution monitoring using AI techniques,” Environmental …, 2022, [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0013935121018752

J. C. Gellers, Rights for Robots: Artificial Intelligence, Animal and Environmental Law (Edition 1). library.oapen.org, 2020. [Online]. Available: https://library.oapen.org/handle/20.500.12657/43332

C. Zhou, Q. Liu, and R. Zeng, “Novel defense schemes for artificial intelligence deployed in edge computing environment,” Wireless Communications and Mobile …. hindawi.com, 2020. [Online]. Available: https://www.hindawi.com/journals/wcmc/2020/8832697/

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Published

2023-10-10

How to Cite

Shino, Y., & Ahsani, H. (2023). Forward Chaining Method Implementation for AI-Powered Passenger Ojek Online and Drive Solutions. IAIC Transactions on Sustainable Digital Innovation (ITSDI), 5(1), 58–66. https://doi.org/10.34306/itsdi.v5i1.610

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Articles