Energy-Efficient Clusters for Object Tracking Networks
Smart cities have hundreds of thousands of devices for tracking data on crime, the environment, and traffic (such as data collected at crossroads and on streets). This results in higher energy usage, as they are recording information persistently and simultaneously. Moreover, a single object trackin...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2018-08-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1996-1073/11/8/2015 |
| _version_ | 1811184634924367872 |
|---|---|
| author | Yang-Hsin Fan |
| author_facet | Yang-Hsin Fan |
| author_sort | Yang-Hsin Fan |
| collection | DOAJ |
| description | Smart cities have hundreds of thousands of devices for tracking data on crime, the environment, and traffic (such as data collected at crossroads and on streets). This results in higher energy usage, as they are recording information persistently and simultaneously. Moreover, a single object tracking device, on a corner at an intersection for example has a limited scope of view, so more object tracking devices are added to broaden the view. As an increasing number of object tracking devices are constructed on streets, their efficient energy consumption becomes a significant issue. This work is concerned with decreasing the energy required to power these systems, and proposes energy-efficient clusters (EECs) of object tracking systems to achieve energy savings. First, we analyze a current object tracking system to establish an equivalent model. Second, we arrange the object tracking system in a cluster structure, which facilitates the evaluation of energy costs. Third, the energy consumption is assessed as either dynamic or static, which is a more accurate system for determining energy consumption. Fourth, we analyze all possible scenarios of the object’s location and the resulting energy consumption, and derive a number of formulas for the fast computation of energy consumption. Finally, the simulation results are reported. These results show the proposed EEC is an effective way to save energy, compared with the energy consumption benchmarks of current technology. |
| first_indexed | 2024-04-11T13:15:41Z |
| format | Article |
| id | doaj.art-39d1dd0f47db4ebca317ed35e764716a |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T13:15:41Z |
| publishDate | 2018-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-39d1dd0f47db4ebca317ed35e764716a2022-12-22T04:22:24ZengMDPI AGEnergies1996-10732018-08-01118201510.3390/en11082015en11082015Energy-Efficient Clusters for Object Tracking NetworksYang-Hsin Fan0Department of Computer Science and Information Engineering, National Taitung University, Taitung 95092, TaiwanSmart cities have hundreds of thousands of devices for tracking data on crime, the environment, and traffic (such as data collected at crossroads and on streets). This results in higher energy usage, as they are recording information persistently and simultaneously. Moreover, a single object tracking device, on a corner at an intersection for example has a limited scope of view, so more object tracking devices are added to broaden the view. As an increasing number of object tracking devices are constructed on streets, their efficient energy consumption becomes a significant issue. This work is concerned with decreasing the energy required to power these systems, and proposes energy-efficient clusters (EECs) of object tracking systems to achieve energy savings. First, we analyze a current object tracking system to establish an equivalent model. Second, we arrange the object tracking system in a cluster structure, which facilitates the evaluation of energy costs. Third, the energy consumption is assessed as either dynamic or static, which is a more accurate system for determining energy consumption. Fourth, we analyze all possible scenarios of the object’s location and the resulting energy consumption, and derive a number of formulas for the fast computation of energy consumption. Finally, the simulation results are reported. These results show the proposed EEC is an effective way to save energy, compared with the energy consumption benchmarks of current technology.http://www.mdpi.com/1996-1073/11/8/2015object tracking networksenergy savingembedded system |
| spellingShingle | Yang-Hsin Fan Energy-Efficient Clusters for Object Tracking Networks Energies object tracking networks energy saving embedded system |
| title | Energy-Efficient Clusters for Object Tracking Networks |
| title_full | Energy-Efficient Clusters for Object Tracking Networks |
| title_fullStr | Energy-Efficient Clusters for Object Tracking Networks |
| title_full_unstemmed | Energy-Efficient Clusters for Object Tracking Networks |
| title_short | Energy-Efficient Clusters for Object Tracking Networks |
| title_sort | energy efficient clusters for object tracking networks |
| topic | object tracking networks energy saving embedded system |
| url | http://www.mdpi.com/1996-1073/11/8/2015 |
| work_keys_str_mv | AT yanghsinfan energyefficientclustersforobjecttrackingnetworks |