Lost Person Search Area Prediction Based on Regression and Transfer Learning Models
| Autor: | Tomislav Blažević, Tomas Pinjušić, Ljiljana Šerić, Karlo Topić |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Service (systems architecture)
Computer science Calibration (statistics) Geography Planning and Development 0211 other engineering and technologies lcsh:G1-922 02 engineering and technology transfer learning Machine learning computer.software_genre 0202 electrical engineering electronic engineering information engineering Earth and Planetary Sciences (miscellaneous) search and rescue machine learning regression cellular automata simulation Computers in Earth Sciences Search and rescue 021101 geological & geomatics engineering Mountain rescue business.industry Regression analysis Construct (python library) Global Positioning System 020201 artificial intelligence & image processing Artificial intelligence business Transfer of learning computer lcsh:Geography (General) |
| Zdroj: | ISPRS International Journal of Geo-Information, Vol 10, Iss 80, p 80 (2021) ISPRS International Journal of Geo-Information Volume 10 Issue 2 |
| ISSN: | 2220-9964 |
| Popis: | In this paper, we propose a methodology and algorithms for search and rescue mission planning. These algorithms construct optimal areas for lost person search having in mind the initial point of planning and features of the surrounding area. The algorithms are trained on previous search and rescue missions data collected from three stations of the Croatian Mountain Rescue Service. The training was performed in two training phases and having two data sets. The first phase was the construction of a regression model of the speed of walking. This model predicts the speed of walking of a rescuer who is considered a well-trained and motivated person since the model is fitted on a dataset made of GPS tracking data collected from Mountain Rescue Service rescuers. The second phase is the calibration of the model for lost person speed of walking prediction with transfer learning on lost person data. The model is used in the simulation of walking in all directions to predict the maximum area where a person can be located. The performance of the algorithms was analysed with respect to a small dataset of archive data of real search and rescue missions that was available and results are discussed. |
| Databáze: | OpenAIRE |
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