International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Real-Time Parking Occupancy Detection Using Statistical Parametric Mapping on an Arduino Edge AI Platform |
|---|---|
| ABSTRACT | The growing demand for efficient urban parking management has accelerated the need for intelligent, low-cost, and real-time monitoring solutions. This paper presents the design and implementation of a real-time parking occupancy detection system based on Statistical Parametric Mapping (SPM) deployed on an Arduino-based Edge AI platform. The proposed system leverages lightweight image processing and statistical modeling techniques to analyze spatial variations in parking slot images and accurately determine occupancy status under varying environmental conditions. By integrating SPM with edge computing principles, the system minimizes latency, reduces dependence on cloud infrastructure, and ensures data privacy. The Arduino platform, combined with optimized algorithms, enables deployment on resource-constrained hardware while maintaining reliable detection performance. Experimental results demonstrate that the system achieves consistent accuracy in real-time scenarios with low power consumption, making it suitable for scalable smart parking applications in urban environments. The proposed approach offers a cost-effective and efficient alternative to conventional cloud-based parking management systems. |
| AUTHOR | DR.M.KARTHIKEYAN, LOKA SABARI S T, GAUTHAM S, MANOGAR V, DHARSHAN J Assistant Professor, Dept. of ECE, Mahendra College of Engineering, Salem, India UG Students, Dept. of ECE, Mahendra College of Engineering, Salem, India |
| VOLUME | 183 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1404126 |
| pdf/126_Real-Time Parking Occupancy Detection Using Statistical Parametric Mapping on an Arduino Edge AI Platform.pdf | |
| KEYWORDS | |
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