APA 6th Edition Stojkoska, B.L., Davcev, D.P. i Trajkovik, V. (2008). N-Queens-based Algorithm for Moving Object Detection in Distributed Wireless Sensor Networks. Journal of computing and information technology, 16 (4), 325-332. https://doi.org/10.2498/cit.1001401
MLA 8th Edition Stojkoska, Biljana L., et al. "N-Queens-based Algorithm for Moving Object Detection in Distributed Wireless Sensor Networks." Journal of computing and information technology, vol. 16, br. 4, 2008, str. 325-332. https://doi.org/10.2498/cit.1001401. Citirano 08.03.2021.
Chicago 17th Edition Stojkoska, Biljana L., Danco P. Davcev i Vladimir Trajkovik. "N-Queens-based Algorithm for Moving Object Detection in Distributed Wireless Sensor Networks." Journal of computing and information technology 16, br. 4 (2008): 325-332. https://doi.org/10.2498/cit.1001401
Harvard Stojkoska, B.L., Davcev, D.P., i Trajkovik, V. (2008). 'N-Queens-based Algorithm for Moving Object Detection in Distributed Wireless Sensor Networks', Journal of computing and information technology, 16(4), str. 325-332. https://doi.org/10.2498/cit.1001401
Vancouver Stojkoska BL, Davcev DP, Trajkovik V. N-Queens-based Algorithm for Moving Object Detection in Distributed Wireless Sensor Networks. Journal of computing and information technology [Internet]. 2008 [pristupljeno 08.03.2021.];16(4):325-332. https://doi.org/10.2498/cit.1001401
IEEE B.L. Stojkoska, D.P. Davcev i V. Trajkovik, "N-Queens-based Algorithm for Moving Object Detection in Distributed Wireless Sensor Networks", Journal of computing and information technology, vol.16, br. 4, str. 325-332, 2008. [Online]. https://doi.org/10.2498/cit.1001401
Sažetak The main constraint of wireless sensor networks (WSN) in enabling wireless image communication is the high energy requirement, which may exceed even the future capabilities of battery technologies. In this paper we have shown that this bottleneck can be overcome by developing local in-network image processing algorithm that offers optimal energy consumption. Our algorithm is very suitable for intruder detection applications. Each node is responsible for processing the image captured by the video sensor, which consists of NxN blocks. If an intruder is detected in the monitoring region, the node will transmit the image for further processing. Otherwise, the node takes no action. Results provided from our experiments show that our algorithm is better than the traditional moving object detection techniques by a factor of (N/2) in terms of energy savings.