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Probabilistic Detection of Indoor Events Using a Wireless Sensor Network-Based Mechanism.
Lial Raja Al-Zabin1, Ola A Al-Wesabi2, Hamed Al Hajri1
1Information Technology Department, Al-Zahra College for Women, Muscat 3365, Oman.
Sensors (Basel, Switzerland)
|August 12, 2023
Summary
This study introduces Probabilistic Collaborative Event Detection (PCED) for wireless sensor networks (WSNs). PCED enhances event detection accuracy and reduces false alarms by using a probabilistic approach with heterogeneous sensors and fuzzy logic.
Area of Science:
- Computer Science
- Electrical Engineering
- Network Engineering
Background:
- Wireless sensor networks (WSNs) are crucial for event detection and environmental monitoring.
- Existing event detection methods often rely on static thresholds, leading to imprecise readings and false alarms.
- Fuzzy logic has been used to mitigate fluctuating sensor data but faces challenges with heterogeneous sensors and complexity.
Purpose of the Study:
- To propose a novel hybrid event detection technique, Probabilistic Collaborative Event Detection (PCED), for clustered WSNs.
- To address the limitations of existing methods, particularly concerning heterogeneous sensors and fuzzy logic complexity.
- To improve the accuracy and reliability of event detection in WSNs.
Main Methods:
- PCED employs a cluster WSN topology.
- It utilizes a probabilistic technique to convert heterogeneous sensor values into probability formulas.
- A Cluster Head Decision Mechanism aggregates sensor data, and fuzzy logic is applied at the fusion center for enhanced precision.
Main Results:
- PCED demonstrated improved probability of detection and reduced probability of false alarms.
- Compared to established mechanisms like REFD, PCED reduced false alarms from 37 to 3 in specific scenarios.
- Detection accuracy improved by up to 19.4%, and detection latency decreased by up to 17.5%.
Conclusions:
- The proposed PCED approach effectively enhances event detection in WSNs, especially with heterogeneous sensors.
- PCED offers a significant reduction in false alarms and improved detection accuracy and latency.
- This method provides a robust solution for event detection applications utilizing WSNs.
