Anomaly detection in the home with seismic sensors | |
| Author | Siraphat Boonchan |
| Call Number | AIT Thesis no.DSAI-22-02 |
| Subject(s) | Anomaly detection (Computer security) Artificial intelligence--Data processing Deep learning (Machine learning) |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Data Science and Artificial Intelligence |
| Publisher | Asian Institute of Technology |
| Abstract | Falls are a global public health problem. Falls happen to people of all ages, especially on the elderly. Throughout the last decade, we have seen improvements in fall detection system due to technology development and the revolution of deep learning. However, using vibration signal analysis can compensate the weakness and also overcomes the drawbacks associated with the traditional system, and this is a novel idea that needs to be studied further. This thesis studies the embedded system and design space for unsupervised anomaly detection model using modern deep learning best practices. The performance and effectiveness of this system to immediately send alert message to user via LINE apllication when abnormal events occur. Accordingly, this study can help the home residents when an anomolous event or falling down event is occurring. |
| Year | 2022 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Data Science and Artificial Intelligence (DSAI) |
| Chairperson(s) | Dailey, Matthew N. |
| Examination Committee(s) | Mongkol Ekpanyapong;Chaklam Silpasuwanchai |
| Scholarship Donor(s) | Royal Thai Government Fellowship |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2022 |