# Distributed Visual Crowdsensing Framework for Area Coverage in Resource Constrained Environments
## 4 Performance Evaluation
### Simulation Results
#### 4.2.6 Power Consumption  
The power consumption of the nodes within the network was evaluated through the radio power model applied in the LEACH protocol [26]. The energy consumption of the transmitter (\(E_{Tx}\)) and the receiver (\(E_{Rx}\)) to send a \(k\)-bit packet can be calculated using the following equations:  
\[E_{Tx}(k,d)=(E_{elec}\times k)+\varepsilon_{amp}\times k\times d^{2}\,\ \ d<d_{0} \tag{5}\]  
\[E_{Tx}(k,d)=(E_{elec}\times k)+\varepsilon_{amp}\times k\times d^{4}\,\ \ d\geq d_{0} \tag{6}\]  
\[E_{Rx}(k)=E_{elec}\times k \tag{7}\]  
where \(E_{dec}\) = 50 nJ/bit, \(\varepsilon_{amp}\)= 100 pJ/bit/m\({}^{2}\), and \(d_{0}\) = 86.2 m.  
We assume the location of the command center is outside the target area (the distance between nodes and the command center is greater than 100 m). Next, the total power consumption of SN-to-SN traffic and SN-to-C traffic for both systems is discussed. Figure 16 shows the total power consumption for both systems, whereby the power consumption is akin to the total (SN-to-SN and SN-to-C) traffic in Figure 13. As evidenced, the proposed system consumes less power, owing to the fact that the proposed system reported lower SN-to-SN and SN-to-C traffic. Hence, the proposed system is superior to the Pols scheme in terms of power consumption and the utility of the photos in general; specifically, it consumes less power and has a higher utility of the photos. Figure 15: Total traffic reduction of the proposed scheme compared to the Pols scheme. * [PERSON] et al. (2016) [PERSON]; [PERSON]; [PERSON]; [PERSON] SmartPhoto: A resource-aware crowd-sourcing approach for image sensing with smartphones. _IEEE Trans. Mob. Comput._**2016**, _15_, 1249-1263. [CrossRef]
* [PERSON] et al. (2016) [PERSON]; [PERSON], [PERSON]; [PERSON], [PERSON]; [PERSON]; [PERSON], [PERSON] Picpick: A generic data selection framework for mobile crowd photography. _Pers. Ubiquitous Comput._**2016**, _20_, 325-335. [CrossRef]
* [PERSON] et al. (2015) [PERSON]; [PERSON], [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON], [PERSON] Fliermeet: A mobile crowdsensing system for cross-space public information reposting, tagging, and sharing. _IEEE Trans. Mobile Comput._**2015**, _14_, 2020-2033. [CrossRef]
* [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON]; [PERSON] CrowdTracking: Real-time vehicle tracking through mobile crowdsensing. _IEEE Internet Things J._**2019**, \(6\), 7570-7583. [CrossRef]
* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON] 2D object recognition: A comparative analysis of SIFT, SURF and ORB feature descriptors. _Multimed. Tools Appl._**2021**, _80_, 18839-18857. [CrossRef]
* [PERSON] et al. (2014) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Deep learning for content-based image retrieval: A comprehensive study. In Proceedings of the ACM International Conference on Multimedia, Orlando, FL, USA, 3-7 November 2014. * [PERSON] et al. (2010) [PERSON]; [PERSON]; [PERSON] Crowdsearch: Exploiting crowds for accurate real-time image search on mobile phones. In Proceedings of the ACM MobiSys, San Francisco, CA, USA, 15-18 June 2010. * [PERSON] et al. (2016) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Resource-aware photo crowdsourcing through disruption tolerant networks. In Proceedings of the 36 th International Conference on Distributed Computing Systems (ICDCS), IEEE, Nara, Japan, 26-30 June 2016; pp. 374-383. * [PERSON] et al. (2016) [PERSON]; [PERSON]; [PERSON] Coopersense: A cooperative and selective picture forwarding framework based on tree fusion. _Int. J. Distrib. Sens. Netw._**2016**, _12_, 6968014. [CrossRef]
* [PERSON] et al. (2017) [PERSON]; [PERSON]; [PERSON] Photo crowdsourcing for area coverage in resource constrained environments. In Proceedings of the INFOCOM 2017-IEEE Conference on Computer Communications, IEEE, Atlanta, GA, USA, 1-4 May 2017. * [PERSON] et al. (2014) [PERSON]; [PERSON]; [PERSON] Opportunities in mobile crowd sensing. _IEEE Commun. Mag._**2014**, _52_, 29-35. [CrossRef]
* [PERSON] et al.