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The aim of the research work presented in this paper is to investigate a mechanism that can recognise high level activities (for example, going for a walk, travelling on the bus, doing evening activity, etc.) and behaviour of low entropy people (people with regular daily life routines, e.g. elderly people with dementia, patients with regular routines) in order to help them improve their health related daily life activities by using wireless proximity data (e.g. Bluetooth, Wi‐Fi).

The paper adopted a tiered approach to recognise activities and behaviour. Higher level activities are divided into sub‐activities and tasks. Separating the tasks from the raw wireless proximity data is achieved by designing task separator (TASE) algorithm. TASE takes wireless proximity data as an input and separates it into different tasks. These detected tasks and the high level daily activity plans that are made in a planning language Asbru, are then fed into the activity recogniser that compares the detected tasks with the plans and recognises the high level activities that the user is performing.

The paper provides an insight to how only wireless proximity data can be utilised to recognise high level activities and behaviour of individuals. A number of scenarios and experiments are designed to prove the validity of the proposed methodology.

This paper focussed on relatively low entropy individuals with regular routines and behavioural patterns which can be improved by increasing the level of entropies in behavioural routines.

The paper includes implications for the utilisation in health care environments for elderly people and physically impaired individuals.

This paper provides a detailed and original study of algorithms and techniques that can be used to recognise high level activities and behaviour of individuals by using only wireless proximity data.

Recognizing daily life activities and human behaviour from contextual information is a challenging task. The purpose of the research work in this paper is to develop a system that can detect indoor and outdoor daily life activities of low entropy mobile people such as elderly people and patients with regular routines using non-intrusive sensor and contextual information.

A framework is proposed that utilises a hierarchical approach in which high-level activities are divided into sub-activities and tasks and recognises the high-level outdoor and indoor activities of daily life. Tasks are recognised at lower level from sensor data and then used by the “activity recogniser” at higher level to recognise the high-level activities. For outdoor activities recognition, wireless proximity data are used, whereas for indoor activities, object usage data obtained through radio frequency identification sensors are used.

For outdoor tasks, results have shown 100 per cent recognition for experiment 1 and a decrease in recognition from 100 to 82.7 per cent, respectively, for experiment 2-9 due to increase in the entropy of individual tasks. Outdoor activity recognition ranges from 84.1 to 100 per cent. For indoor tasks, generating alternative tasks sequences approach effectively recognised the single tasks that were conducted with objects without any order. Average indoor activity recognition rate remains above 90 per cent. The reason why this approach is able to detect the activities without their distinct features is the planning capability of the Asbru that is used in the modelling of high-level activities.

The novelty of this research work is a framework that utilises different types of sensor data and recognises both indoor and outdoor daily life activities of individuals.

The purpose of this work is to assess the influence of ambient noise on the performance of wireless sensor networks (WSNs) empirically and, based on these findings, develop a mathematical tool to assist technicians to determine the maximum inter-node separation before deploying a new WSN.

A WSN test platform is set up in an electromagnetically shielded environment (RF chamber) to accurately control and quantify the ambient noise level. The test platform is subsequently placed in an operational laboratory to record network performance in typical unshielded spaces. Results from the RF chamber and the real-life environments are analysed.

A minimum signal-to-noise ratio (SNR) at which the network still functions was found to be of the order 30 dB. In the real-life scenarios (machines, telecommunications and computer laboratories), the measured SNR exceeded this minimum value by more than 20 dB. This is due to the low ambient industrial noise levels observed in the 2.4 GHz ISM band for typical environments found at academic institutions. It, therefore, suggests that WSNs are less prone to industrial interferences than anticipated.

A predictive mathematical tool is developed that can be used by technicians to determine the maximum inter-node separation before the WSN is deployed. The tool yields reliable results and promises to save installation time.

This paper aims to present the design and implementation of a circularly polarized co-planar waveguide (CPW) fed wideband pie-shaped monopole antenna for multi-antenna techniques. Multi-antenna techniques are promising solutions for higher data rate and enhanced reliability of wireless applications. They find numerous applications in 4G/5G networks and in most wireless standards such as wireless local area networks (WLAN), wireless fidelity and worldwide interoperability for microwave access systems to enhance the channel capacity without additional spectrum by means of multi-path propagation techniques.

The antenna is designed to operate at three WLAN frequency bands of 4.8, 5.2 and 5.8 GHz. The measured 10 dB impedance bandwidth of the proposed antenna element is 1.2 GHz (24.23 per cent). The proposed CPW fed, pie-shaped monopole antenna has a gain of 5.4 dB and an efficiency of 72.8 per cent at 4.8 GHz.

To use the proposed antenna in a multi-antenna environment, the antennas have to be placed in a close proximity to each other. The close proximity introduces strong mutual coupling between the antennas, which in turn degrades the performance of multi-antenna systems. A multi-antenna system with two antenna elements has been constructed with an edge to edge spacing of 0.24 λ₀ (15 mm), and the mutual coupling level is −17 dB. To enhance the isolation between the antenna elements, a shorting pin-based interconnected semicircles enclosed decoupling structure is proposed, which improves the isolation by a factor of 12.67 dB at 4.8 GHz.

To validate the performance of the proposed multi-antenna in working environment, the performance metrics such as envelope correlation coefficient (ECC), diversity gain (DG) and total active reflection coefficient (TARC) are computed for the proposed multiple-input multiple-output (MIMO) antenna. The ECC value is 0.000366 at center frequency and below 0.09 for the entire operating bandwidth, which is well below the acceptable level of 0.5 as per 3GPP standard. The DG value lies above 9.5 dB for the entire operating bandwidths and it is well above the minimum value of 3 dB. The TARC values are calculated based on S parameters, and it proves that the proposed antenna a good candidate for the multi-antenna systems.

The purpose of this study is to locally develop low-cost wireless mesh networks for reliable data communications to devices that prevent the theft of these devices in learning institutions of South Africa.

A network test-bench was developed where millions of packets were transmitted and logged between interconnected nodes to analyze the quality of the network’s service in a harsh indoor building environment. Similar methodologies in “big data” analysis as found in particle physics were adopted to analyze the network’s performance and reliability.

The results from statistical analysis reveal the quality of service between multiple asynchronous transmitting nodes in the network and compared with the wireless technology routing protocol to assess coverage in large geographical areas. The mesh network provides stable data communications between nodes with the exception of reliability degradation in some multi-hopping routes. Conclusions are presented to determine whether the underlining mesh network technology will be deployed to protect devices against theft in educational institutions of South Africa.

The anti-theft application will focus on proprietary firmware development with a reputable tablet manufacturer to render the device inoperable. Data communications of devices to the network will be monitored and controlled from a central management system. The electronics embedding the system-on-chip will be redesigned and developed using the guidelines stipulated by the chip manufacturer.

Design and development of low-cost wireless mesh networks to protect tablets against theft in institutions of digitized learning. The work presents performance and reliability metrics of a low-power wireless mesh wireless technology developed in a harsh indoor building environment.

Wireless communication channel provides a wide area of applications in the field of communication, distributed sensor network and so on. The prominence of the wireless communication channel is because of its robust nature and the sustainability for the precise ranging and the localization. The precision and accuracy of the wireless communication channel largely depend on the localization. The development of the wireless communication channel with improved benefits needs the accurate channel model.

This paper characterizes the tangential path loss model in the WINNER based wireless communication channel model. The measurements taken in the WINNER channel model are compared with the tangential path loss characterized WINNER Channel model.

The model operates well over the varying antenna orientations, measurement condition and the propagation condition. The proposed tangential path loss model is performing well over the various outdoor scenarios.

The proposed characterization shows change in the small-scale parameters (SSP), such as power, delay, angle of arrival and angle of departure as well as the large-scale parameters (LSP), such as RMS delay spread, shadowing, path loss and Ricean factor associated with the model.

Playing games over the wireless Internet is significantly more dangerous than using traditional wired networks. Wireless networks offer new hackers new ways to attack. Since there is no physical connection for wireless networks, it is also more difficult to prevent attacks or locate the attackers. This paper will review the unique threats inherent in the wireless gaming environment and present a model aimed at solving these problems.

This paper has proposed a Fog architecture-based framework, which classifies dengue patients into uninfected, infected and severely infected using a data set built in 2010. The aim of this proposed framework is to developed a latency-aware system for classifying users into different categories based on their respective symptoms using Internet of Things (IoT) sensors and audio and video files.

To achieve the aforesaid aim, a smart framework is proposed, which consist of three components, namely, IoT layer, Fog infrastructure and cloud computing. The latency of the system is reduced by using network devices located in the Fog infrastructure. Data generated by IoT layer will first be processed by Fog layer devices which are in closer proximity of the user. Raw data and data generated will later be stored on cloud infrastructure, from where it will be sent to different entities such as user, hospital, doctor and government healthcare agencies.

Experimental evaluation proved the hypothesis that using the Fog infrastructure can achieve better response time for latency sensitive applications with the least effect on accuracy of the system.

The proposed Fog-based architecture can be used with IoT to directly link it with the Fog layer.

This research investigated the feasibility of using an inductively coupled antenna as the basis of applying a systems approach to smart clothing. In order to simulate real-life situations, the impact of the distortions and relative displacement of different fabric layers (with affixed antennas) on the signal quality was assessed. The paper aims to discuss these issues.

A spiral antenna was printed on different fabric substrates. Obstructive conditions of the inductively coupled fabric layers were investigated to find out how much influence these conditions had on transmission performance. Reflected signals and transmitted signals were observed, while fabric antennas were subjected to displacement (distance and dislocation) or deformation (stretching and bending). The threshold of physical obstacles was estimated based on statistical analyses.

The limits of physical conditions that enable proper wireless transmission were estimated up to ∼2 cm for both distance and dislocation, and ∼0.24 K for bending deformation. The antenna performance remained within an acceptable level of 20 percent transmission up to 10 percent fabric stretch. Based on well-established performance metrics used in clothing environment on the body, which employs 2-5 cm of ease, the results imply that the inductively coupled antennas may be suitable for use in smart clothing.

This research demonstrates that the use of inductively coupled antennas on multiple clothing layers could offer the basis of a new “wireless” system approach to smart clothing. This would not only result in performance benefits, but would also significantly improve the aesthetics of smart clothing which should result in new markets for such products.