Semantic-aware anomaly detection in real time parking data
A Bhattacharyya, W Wang, C Tsang… - 2017 IEEE 15th …, 2017 - ieeexplore.ieee.org
A Bhattacharyya, W Wang, C Tsang, C Amza
2017 IEEE 15th International Conference on Industrial Informatics …, 2017•ieeexplore.ieee.orgIn this work, we introduce and experimentally evaluate a novel approach for real time
anomaly detection in smart car parking applications. We attach semantics on top of raw real
time parking data collected from sensors of parking lots. We use knowledge from historical
data to detect anomalies on real time data. Attaching semantics on top of raw data helps
reduce the learning time by a factor of 3.1 x and also provides the error checker a distinct
context to look into potential problems.
anomaly detection in smart car parking applications. We attach semantics on top of raw real
time parking data collected from sensors of parking lots. We use knowledge from historical
data to detect anomalies on real time data. Attaching semantics on top of raw data helps
reduce the learning time by a factor of 3.1 x and also provides the error checker a distinct
context to look into potential problems.
In this work, we introduce and experimentally evaluate a novel approach for real time anomaly detection in smart car parking applications. We attach semantics on top of raw real time parking data collected from sensors of parking lots. We use knowledge from historical data to detect anomalies on real time data. Attaching semantics on top of raw data helps reduce the learning time by a factor of 3.1x and also provides the error checker a distinct context to look into potential problems.
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