Smart Automated Zebra Crossing System Using PIR Sensors, IoT Integration, and IP Camera-Based Headcount for Enhanced Road Safety
The Smart Automated Zebra Crossing System operationalizes Passive Infrared (PIR) sensors and Internet of Things (IoT) technology with IP camera-based headcount capabilities to foster pedestrian safety. A data-driven control system protected pedestrian safety by integrating adaptive management structures and intelligent traffic methods. The system actively switches on its crossing systems only after PIR sensors detect approaching pedestrians. IP cameras enabled by advanced computer vision algorithms provide real-time pedestrian counting and density measurement services. Networks based on IoT technology carry system data to produce shifting crosswalk time lengths through dynamic adjustments based on variations in pedestrian numbers. Smart LED warning indicators inform drivers about traffic while adaptive timing systems shorten the time pedestrians and drivers need to wait. Real-time decision capabilities and reduced web dependence emerge from the system's edge computing architecture which ensures operational reliability. Through solar power technology all system components underwent upgrades to become durable in varying weather conditions and maintain sustainable operation in any environment. The gathered system data helps analytical experts predict dangerous traffic areas and peak times which supports better precautionary traffic management and future infrastructure development strategies. This modern framework takes pedestrian safety to new heights while efficiently utilizing roads through combination of real-time detection systems and dynamic adaptiveness with data analytical features. Researchers studied architectural elements of the system together with implementation methods and performance results in order to show how this technology will transform smart transportation infrastructure in the future.
Authors
- G. Adiline Macriga (ORCID: https://orcid.org/0000-0002-8675-1838)
- Enbo Ma (ORCID: https://orcid.org/0000-0001-6320-9360)
Institutions
- Sri Sai University (IN)
Publication Details
- Published
- 2025-04-16
- DOI
- https://doi.org/10.1109/iccct63501.2025.11019033
- Primary Topic
- Autonomous Vehicle Technology and Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.00