| Autor: |
Zadorozhnyi, Oleksandr, Tsiantis, Pavlos, Michaelides, Erricos, Constantinou, Christos C., Kyriakides, Ioannis, Alexopoulos, Ilias, Abdi, Ehson, Reodica, Jerald, Hayes, Daniel R. |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) |
| DOI: |
10.5281/zenodo.7645870 |
| Popis: |
Marine surveillance deals with the complex problemof modeling and estimating natural and human processeswhile operating with limited information acquisition resources.The complexity of the problem and the scarcity of resources,such as power, processing, and communications, requires agiledistributed sensing and computing that provides scalability,diversity in information acquisition, and adaptive allocationof limited resources. This work deals with tracking multiplemarine vehicles using data from heterogeneous sensors. Accuratetracking is achieved by a synergy between a network of agilemaritime IoTs, with limited processing resources, and a fusion center, with computationally intensive capability. The IoTs canreconfigure their elementary processing operations settings toproduce informative yet low volume measurement statistics. Thefusion center handles heterogeneous data fusion and solves thecomplex problem of vehicle state estimation. We demonstratethat by configuring its agile distributed computing capabilities,the proposed system provides significant savings in processingand communications resources without deteriorating trackingperformance. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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