IMPROVING ENERGY EFFICIENCY OF WIRELESS CAMERA NETWORKS BASED ON IEEE 802.15.4 STANDARD
In this paper is proposed a method, which helps to increase the energy efficiency of wireless camera sensor networks. The method is based on image recognition on low-power end devices of the system.
Currently, wireless sensor networks (WSN) are used in many areas of medicine, especially where there is a need for constant monitoring of the patient's condition. However, in many cases, the lack of technical resources for processing information does not allow monitoring the patients' condition in the necessary way. Also, there are difficulties in monitoring the status of patients on outpatient treatment everywhere.
It is considered the model of large monitoring networks with working independently sensors for an alarm signalization. Outlined in the previous papers the method of group polling for alarming sensors identification used the time synchronization. The last condition is very strong for vide distributed monitoring networks. Recently proposed method of group polling for the alarming sensors identification in unsynchronized wireless monitoring network is investigated. Based on numerical simulations, it is found that the group polling method may be effective for unsynchronized networks with thousands or more sensors and the decoding algorithm may be realized on-time using parallel executions. Recommended number of the code signal repetitions is proposed.
Distinguishing outliers from normal data in wireless sensor networks has been a big challenge in the anomaly detection domain, mostly due to the nature of the anomalies, such as software or hardware failures, reading errors or malicious attacks, just to name a few. In this article, we introduce an anomaly detection-based OPF classifier in the aforementioned context. The results are compared against one-class support vector machines and multivariate Gaussian distribution. Additionally, we also propose to employ meta-heuristic optimization techniques to finetune the OPF classifier in the context of anomaly detection in wireless sensor networks.
This book constitutes the refereed proceedings of the 7th International Workshop on Multiple Access Communications, MACOM 2014, held in Halmstad, Sweden, in August 2014. The 12 full papers presented were carefully reviewed and selected from 22 submissions. They describe the latest advancements in the field of multiple access communications with an emphasis on reliability issues, physical layer techniques, cognitive radio, medium access control protocols, and video coding.
This book constitutes the refereed proceedings of the 12th International Conference on Parallel Computational Technologies, PCT 2018, held in Rostov-on-Don, Russia, in April 2018.
The 24 revised full papers presented were carefully reviewed and selected from 167 submissions. The papers are organized in topical sections on high performance architectures, tools and technologies; parallel numerical algorithms; supercomputer simulation.