An Overview and Assessment of Wireless Technologies and Co- existence of ZigBee, Bluetooth and Wi-Fi Devices

AbstractWi-Fi, ZigBee and Bluetooth wireless communication systems utilize the Industrial Scientific and Medical-(ISM) Band, which results in a high mutual interference between these technologies since they all these systems operate at the same or very close frequency bands. The interference problem increases with an in-device Co-existence (technologies existing on same device). This is primarily due to the characteristics of each technology such as access mechanism, frame structure, peak transmit power and frequency of operation. This work describes the interference between the Wi-Fi mostly as an aggressor on Bluetooth and ZigBee wireless networks. So the experimental analysis of the coexistence of these three technologies in an assumed home environment is studied especially when ZigBee is enabled for a Home Automation Network where there could be close proximity of Wi-Fi and Bluetooth devices such as PDAs and mobile phones. The obtained result shows that there is severe degradation on ZigBee and Bluetooth packet transmission of packets as well as re-transmission of ZigBee packets when Wi-Fi is operating

On the use of the ZigBee protocol for wireless sensor networks

This project was developed within the ART-WiSe framework of the IPP-HURRAY group (http://www.hurray.isep.ipp.pt), at the Polytechnic Institute of Porto (http://www.ipp.pt). The ART-WiSe – Architecture for Real-Time communications in Wireless Sensor networks – framework (http://www.hurray.isep.ipp.pt/art-wise) aims at providing new communication architectures and mechanisms to improve the timing performance of Wireless Sensor Networks (WSNs). The architecture is based on a two-tiered protocol structure, relying on existing standard communication protocols, namely IEEE 802.15.4 (Physical and Data Link Layers) and ZigBee (Network and Application Layers) for Tier 1 and IEEE 802.11 for Tier 2, which serves as a high-speed backbone for Tier 1 without energy consumption restrictions. Within this trend, an application test-bed is being developed with the objectives of implementing, assessing and validating the ART-WiSe architecture. Particularly for the ZigBee protocol case; even though there is a strong commercial lobby from the ZigBee Alliance (http://www.zigbee.org), there is neither an open source available to the community for this moment nor publications on its adequateness for larger-scale WSN applications. This project aims at fulfilling these gaps by providing: a deep analysis of the ZigBee Specification, mainly addressing the Network Layer and particularly its routing mechanisms; an identification of the ambiguities and open issues existent in the ZigBee protocol standard; the proposal of solutions to the previously referred problems; an implementation of a subset of the ZigBee Network Layer, namely the association procedure and the tree routing on our technological platform (MICAz motes, TinyOS operating system and nesC programming language) and an experimental evaluation of that routing mechanism for WSNs

Exploiting programmable architectures for WiFi/ZigBee inter-technology cooperation

The increasing complexity of wireless standards has shown that protocols cannot be designed once for all possible deployments, especially when unpredictable and mutating interference situations are present due to the coexistence of heterogeneous technologies. As such, flexibility and (re)programmability of wireless devices is crucial in the emerging scenarios of technology proliferation and unpredictable interference conditions. In this paper, we focus on the possibility to improve coexistence performance of WiFi and ZigBee networks by exploiting novel programmable architectures of wireless devices able to support run-time modifications of medium access operations. Differently from software-defined radio (SDR) platforms, in which every function is programmed from scratch, our programmable architectures are based on a clear decoupling between elementary commands (hard-coded into the devices) and programmable protocol logic (injected into the devices) according to which the commands execution is scheduled. Our contribution is two-fold: first, we designed and implemented a cross-technology time division multiple access (TDMA) scheme devised to provide a global synchronization signal and allocate alternating channel intervals to WiFi and ZigBee programmable nodes; second, we used the OMF control framework to define an interference detection and adaptation strategy that in principle could work in independent and autonomous networks. Experimental results prove the benefits of the envisioned solution

Water Pipeline Leakage Detection Based on Machine Learning and Wireless Sensor Networks

The detection of water pipeline leakage is important to ensure that water supply networks can operate safely and conserve water resources. To address the lack of intelligent and the low efficiency of conventional leakage detection methods, this paper designs a leakage detection method based on machine learning and wireless sensor networks (WSNs). The system employs wireless sensors installed on pipelines to collect data and utilizes the 4G network to perform remote data transmission. A leakage triggered networking method is proposed to reduce the wireless sensor network’s energy consumption and prolong the system life cycle effectively. To enhance the precision and intelligence of leakage detection, we propose a leakage identification method that employs the intrinsic mode function, approximate entropy, and principal component analysis to construct a signal feature set and that uses a support vector machine (SVM) as a classifier to perform leakage detection. Simulation analysis and experimental results indicate that the proposed leakage identification method can effectively identify the water pipeline leakage and has lower energy consumption than the networking methods used in conventional wireless sensor networks

Characterization of the on-body path Loss at 2.45 GHz and energy efficient WBAN design for dairy cows

Wireless body area networks (WBANs) provide promising applications in the healthcare monitoring of dairy cows. The characterization of the path loss (PL) between on-body nodes constitutes an important step in the deployment of a WBAN. In this paper, the PL between nodes placed on the body of a dairy cow was determined at 2.45 GHz. Finite-difference time domain simulations with two half-wavelength dipoles placed 20 mm above a cow model were performed using a 3-D electromagnetic solver. Measurements were conducted on a live cow to validate the simulation results. Excellent agreement between measurements and simulations was achieved and the obtained PL values as a function of the transmitter-receiver separation were well fitted by a lognormal PL model with a PL exponent of 3.1 and a PL at reference distance ( 10 cm) of 44 dB. As an application, the packet error rate ( PER) and the energy efficiency of different WBAN topologies for dairy cows (i.e., single-hop, multihop, and cooperative networks) were investigated. The analysis results revealed that exploiting multihop and cooperative communication schemes decrease the PER and increase the optimal payload packet size. The analysis results revealed that exploiting multihop and cooperative communication schemes increase the optimal payload packet size and improve the energy efficiency by 30%

Advanced real-time indoor tracking based on the Viterbi algorithm and semantic data

A real-time indoor tracking system based on the Viterbi algorithm is developed. This Viterbi principle is used in combination with semantic data to improve the accuracy, that is, the environment of the object that is being tracked and a motion model. The starting point is a fingerprinting technique for which an advanced network planner is used to automatically construct the radio map, avoiding a time consuming measurement campaign. The developed algorithm was verified with simulations and with experiments in a building-wide testbed for sensor experiments, where a median accuracy below 2 m was obtained. Compared to a reference algorithm without Viterbi or semantic data, the results indicated a significant improvement: the mean accuracy and standard deviation improved by, respectively, 26.1% and 65.3%. Thereafter a sensitivity analysis was conducted to estimate the influence of node density, grid size, memory usage, and semantic data on the performance