Two-Way Tracking System for Buses Augmented by Intelligent Sensor and VLSI Technology: A Study
Keywords:
Bus, Bus route, Bus tracking, GPS, Location, Sensors, Two-way tracking system, VLSIAbstract
Daily commute, especially for students and professionals relying on public transport, often comes with an element of uncertainty. Where is the bus? Will it be on time? Is it safe? These questions, once the source of considerable anxiety, are now being decisively answered by innovative solutions. One such breakthrough is the two-way tracking system for buses, augmented by intelligent sensor technology. This advanced system transcends the limitations of traditional, unidirectional GPS tracking, ushering in an era of unprecedented transparency, safety, and operational efficiency for bus services. Historically, bus tracking systems have been rudimentary at best. Passengers are left guessing, parents of school children worry, and dispatchers operate with limited real-time information. The two-way tracking system, integrated with a suite of sensors, addresses these issues head-on by creating a dynamic communication loop between the bus, a central control system, and – crucially – the end-users (passengers and parents). While basic GPS tracking has been around for some time, the "two-way" aspect, combined with advanced sensor integration, elevates bus management and passenger experience to an entirely new level. The two-way bus tracking system, powered by an intelligent network of sensors run under VLSI technology, is more than just a tracking device. It's a comprehensive information and communication hub that promises to deliver a smarter, safer, and remarkably more efficient public transportation experience for everyone involved. The era of the truly connected bus is here.
References
O. Mulani, “IoT Based Air, Water, and Soil Monitoring System for Pomegranate Farming,” Annals of Agri-bio-Research, vol. 29, no. 2, pp. 71–86, Nov. 2024
N. Upadhyaya, C. Surekha, P. Malathi, and G. Suresh, “Pioneering Cognitive Computing for Transformative Healthcare Innovations,” SSRN Electronic Journal, Jan. 2025
A. A. Kamaraj and D. P. Acharjya, “Explainable Artificial Intelligence in Healthcare Systems,” Computer Science, Technology and Applications, 2024, doi: https://doi.org/10.52305/gomr8163.
O. Mulani, N. Warade, “ML-powered Internet of Medical Things Structure for Heart Disease Prediction,” Journal of Pharmacology and Pharmacotherapeutics, Jan. 2025
M Pradeepa. Student Health Detection using a Machine Learning Approach and IoT, 2022 IEEE 2nd Mysore sub section International Conference (MysuruCon), 2022.
K. Kazi, “Modelling and Simulation of Electric Vehicle for Performance Analysis,” Advances in Mechatronics and Mechanical Engineering (AMME) book series, pp. 295–320, Mar. 2024
K. Sayyad, S. S. Shinde, P. M. Nerkar, S. S. Kazi, and V. S. Kazi, “Machine Learning for Brand Protection,” Advances In Marketing, Customer Relationship Management, And E-Services Book Series, pp. 175–220, Jan. 2025.
K. SayyadLiyakat Kazi, “Computer-Aided Diagnosis in Ophthalmology,” Advances in Healthcare Information Systems and Administration Book Series, pp. 112–135, Feb. 2024
P. Mangesh Nerkar and Kazi, “Predictive Data Analytics Framework Based on Heart Healthcare System (HHS) Using Machine Learning,” Journal of Advanced Zoology, 2023.
P. H B, and L. Pujari, “Machine Learning Approaches for Company Share Rate Prediction,” GRENZE International Journal of Engineering and Technology, 2026. https://thegrenze.com/index.php?display=page&view=journalabstract&absid=2514&id=8
P. Neeraja, R. G. Kumar, M. S. Kumar, Kazi, and M. S. Vani, “DL-Based Somnolence Detection for Improved Driver Safety and Alertness Monitoring,” 2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT), pp. 589–594, Feb. 2024.
K. Sayyad Liyakat Kazi, “ChatGPT: An Automated Teacher’s Guide to Learning,” Advances in Computational Intelligence and Robotics Book series, pp. 1–20, May 2024.
C. Veena, M. Sridevi, Kazi, B. Saha, S. R. Reddy, and N Shirisha, “HEECCNB: An Efficient IoT-Cloud Architecture for Secure Patient Data Transmission and Accurate Disease Prediction in Healthcare Systems,”: 2023 Seventh International Conference on Image Information Processing (ICIIP), pp. 407–410, Nov. 2023.
K. R. Prasad, S. Rao Karanam, D. Ganesh, and Kazi, “AI in public-private partnership for IT infrastructure development,” The Journal of High Technology Management Research, vol. 35, no. 1, pp. 100496–100496, May 2024.
K. Kutubuddin, S. Liyakat, D. Rajesh, and G. Konnur, “Vehicle Health Monitoring System (VHMS) by Employing IoT and Sensors,” GRENZE International Journal of Engineering and Technology, Jul. 2024.
K. Kazi and S. Liyakat, “A Novel Approach on ML based Palmistry,” GRENZE International Journal of Engineering and Technology, 2024.
K. S. L. Kazi, “Machine Learning-Based Pomegranate Disease Detection and Treatment,” Advances in Environmental Engineering and Green Technologies, pp. 469–498, Jun. 2024.
Kazi Kutubuddin. IoT based Boiler Health Monitoring for Sugar Industries, Grenze International Journal of Engineering and Technology, vol. 10, no. 2, pp. 5178 -5185, 2024.
K. S. Liyakat Kazi, “Machine Learning-Driven Internet of Medical Things (ML-IoMT)-Based Healthcare Monitoring System,” Responsible AI for Digital Health and Medical Analytics, 2025.
K. Kutubuddin and P. Nerkar, “IoT-Based Skin Health Monitoring System,” International Journal of Biology, Pharmacy and Allied Sciences, vol. 13, no. 11, Nov. 2024.
R. Keerthana and V. K, “Machine Learning Based Risk Assessment for Financial Management in Big Data IoT Credit,” Proceedings of the 3rd International Conference on Optimization Techniques in the Field of Engineering (ICOFE-2024), 2025.
O. Srinivas and R. Shanthy, “Artificial Intelligence and Cloud-Enabled E-Vehicle Design with Wireless Sensor Integration,” Proceedings of the 3rd International Conference on Optimization Techniques in the Field of Engineering (ICOFE-2024), 2026.
M. S. Kumar and D. Ganesh, “Deep Convolution Neural Network Based solution for Detecting Plant Diseases,” Journal of Pharmaceutical Negative Results, vol. 13, no. S01, Jan. 2022.
K. Kazi, S. Liyakat, H, “Nanotechnology in IoT Security”, Journal of Nanoscience, Nanoengineering & Applications, vol. 12, no. 3, pp. 11 – 16, 2022.
W. Devanand, R. Raghunath, A. Baliram, K. Kazi, and A. Prof, “Smart Agriculture System Using IoT,” International Journal of Innovative Research in Technology, vol. 5, no. 10, pp. 480-483, 2019
P. Nerkar, S. S. Shinde, K. Kutubuddin, and S. Liyakat, “Monitoring Fresh Fruit and Food Using Iot and Machine Learning to Improve Food Safety and Quality,” Tuijin Jishu/Journal of Propulsion Technology, vol. 44, no. 3, pp. 1001–4055, Oct. 2023.