Abstract
In today's world, sensors play a crucial role, as they feed information to make accurate decisions and take actions; therefore, making sure that sensors behave correctly is critical. In this work, we focus on inspecting the data provided by sensors, aiming at discovering any issue due to malfunction, misuse, or any other source of error before the issue is propagated through the system. To achieve that, we propose a novel approach based on wavelets embedded in a microcontroller to analyze data from sensors. The objective is to determine whether the sensor is issuing correct data (normal behavior) or not (abnormal behavior), to prevent the error from reaching other parts of the system.
| Original language | English |
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| Title of host publication | 2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1718-1723 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781665430654 |
| DOIs | |
| State | Published - 2023 |
| Event | 2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023 - Mexico City, Mexico Duration: 5 Dec 2023 → 8 Dec 2023 |
Publication series
| Name | 2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023 |
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Conference
| Conference | 2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023 |
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| Country/Territory | Mexico |
| City | Mexico City |
| Period | 5/12/23 → 8/12/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- Embedded Systems
- Euclidean distance
- anomaly behavior analysis
- discrete wavelet transform
- sensor's fault detection