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    Novel visible light positioning techniques : a thesis presented in partial fulfilment of the requirements of the degree of Doctor of Philosophy in Department of Mechanical and Electrical Engineering at Massey University, Albany, New Zealand
    (Massey University, 2024-01-31) Chew, Moi Tin
    Localization is the process of finding an object’s position within the space that it is situated in. Localization can be categorised into two types, indoors and outdoors. Outdoor localization is already a matured technology which mainly relies on well-known positioning satellite systems such as Global Positioning System (GPS) and GLObal NAvigation Satellite System (GLONASS). However, the indoor localization is still a growing area of research. Visible Light Positioning (VLP) has been getting the attention of researchers due to several advantageous factors. VLP is more accurate than many of the competing techniques. As Light Emitting Diode (LED) based luminaires have become an integral part of the indoor lighting systems in modern buildings and residences, such lighting infrastructure can be leveraged for localizing objects. The VLP systems are also suitable in places like hospitals and airports due to the fact that LED does not generate electromagnetic interference which can potentially affect the operation of many equipment used in those places. This doctoral research develops novel techniques and applications for VLP, and these are fully supported by experimental results and data analysis. Fingerprinting is a common positioning method used in VLP systems that employs Received Signal Strength (RSS) as the signal characteristics. Weighted K-Nearest Neighbour (WKNN) is one of the most popular algorithms for such localization systems. This thesis investigates the impact of distance metrics used to compute the weights of the WKNN algorithm on the localization accuracy of the VLP. Experimental results show that Squared Chord distance is the most robust and accurate metric and significantly outperforms the commonly used Euclidean distance metric. Robot navigation is one of the many potential applications of VLP. Recent literature shows a small number of works on robots being controlled by fusing location information acquired by VLP that uses rolling shutter effect camera as a receiver with other sensor data. In contrast, this thesis reports the experimental performance of a cartesian robot that was controlled solely by a VLP system using a cheap photodiode-based receiver. Two different methods (Direct Method and Spring Relaxation Method) were developed to leverage the VLP as an online navigation system to control the robot. The experiments consisted of the robot autonomously repeating various paths multiple times. The results show that both methods offer promising accuracy, with Direct Method and Spring Relaxation Method reaching the target positions of median / 90-percentile error of 27.16mm / 37.04mm, and 26.05mm / 47.48mm respectively. The operation of VLP is very much dependent on the line of sight (LOS) link between the luminaires and the receiver. Unfortunately, in a practical environment, luminaires are positioned to serve illumination needs. Therefore, enough luminaires may not be visible for the purpose of positioning the target. One way to compensate this would be to utilise an ultrasound system to eliminate the “blind spots” of the VLP system. The final part of this work consists of a study of the ultrasound based indoor localization. A bespoke system employing an ultrasonic array to transmit chirp signals and time of flight measurement for ranging was developed. The position of the receiver is estimated iteratively using the spring relaxation technique. The spring relaxation technique, which has not been used for ultrasonic localization in the literature, outperforms the widely adopted linear least square-based lateration technique. The experimental results show that the ultrasonic system can be a viable option for fusing with a VLP system.
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    Improving network lifetime through energy-efficient protocols for IoT applications : thesis submitted to the School of Food and Advanced Technology, Massey University New Zealand, in partial fulfilment of the requirements for the degree of Doctor of Philosophy
    (Massey University, 2022) Mishra, Mukesh
    Sensors are ubiquitous. They can be found in homes, factories, farms, and just about everywhere else. To meet distributed sensing requirements several sensors are deployed and connected on a wireless media to form a Wireless Sensor Network (WSN). Sensor nodes exchange information with one another and with a base station (BS). We begin with a review of recent work on cross-layer WSN design techniques based on the Open System Interconnection (OSI) model. The distributed sensor nodes are often grouped in clusters and a cluster head (CH) is chosen and used to route data from the sensor nodes to the BS. The thesis evaluates constraints-based routing algorithms, which choose a routing path that satisfies administrative or Quality of Service (QoS) constraints. Different algorithms reduce costs, balance network load, and improve security. Clustering sensor nodes in a wireless sensor network is an important technique for lowering sensor energy consumption and thus extending the network's lifetime. The cluster head serves as a router in a network. Furthermore, the cluster head is in charge of gathering and transmitting sensed information from cluster members to a destination node or base station/sink. To safely elect a cluster head, an efficient clustering approach is required. It continues to be an important task for overall network performance. As a result, in this study, we propose a scheme for cluster head selection based on a trust factor that ensures all nodes are trustworthy and authentic during communication. Direct trust is calculated using parameters such as residual energy and node distance. Further, K-means clustering algorithm has been employed for cluster head selection. The simulation results show that the proposed solution outperforms the LEACH (Low-Energy Adaptive Clustering Hierarchy) protocol in improving network lifetime, packet delivery ratio, and energy consumption. Furthermore, this strategy can significantly improve performance while discriminating between legitimate and malicious (or compromised) nodes in the network. The use of the IoT in wireless sensor networks (WSNs) presents substantial issues in ensuring network longevity due to the high energy requirements of sensing, processing, and data transmission. Thus, multiple conventional algorithms with optimization methodologies have been developed to increase WSN network performance. These algorithms focus on network layer routing protocols for dependable, energy-efficient communication, extending network life. This thesis proposes multi-objective optimization strategy. It calculates the optimum path for packets from the source to the sink or base station. The proposed model works in two-steps. First, a trust model selects cluster head to control data connection between the BS and cluster nodes. To determine data transmission routes, a novel hybrid algorithm is proposed that combines a particle swarm optimization (PSO) algorithm and a genetic algorithm (GA) .The obtained results validate the proposed approach's efficiency, as it outperforms existing methods in terms of increased energy efficiency, increased network throughput, high packet delivery ratio, and high residual energy across all iterations. Sensor nodes (SNs) have very constrained memory, energy, and computational resources.The limitations are further exacerbated due to the large volume of sensing data generated in a distributed IoT application . Energy can be saved by compressing data at the sensor node or CH level before transmission. The majority of data compression research has been motivated by image and video compression; however, the vast majority of these algorithms are inapplicable on sensor nodes due to memory restrictions, energy consumption, and processing speed. To address this issue, we chose established data compression techniques such as Run Length Encoding (RLE) and Adaptive Huffman Encoding (AHE), which require much less resources and can be executed on sensor nodes. Both RLE and AHE can negotiate compression ratio and energy utilisation effectively. This thesis initially evaluates RLE and AHE data compression efficiency. Hybrid-RLEAHE (H-RLEAHE) is then suggested and tested for sensor nodes. Simulations were run to validate the efficacy of the proposed hybrid algorithm, and the results were compared to compression methods using RLE, AHE, and without the use of any compression technique for five different cases. RLE data compression outperforms H-RLEAHE and AHE in energy efficiency, network performance, packet delivery ratio, and energy across all iterations.
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    Indoor localization utilizing existing infrastructure in smart homes : a thesis by publications presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Computer and Electronics Engineering, Massey University, Albany, New Zealand
    (Massey University, 2019) Konings, Daniel
    Indoor positioning system (IPS) have received significant interest from the research community over the past decade. However, this has not eventuated into widespread adoption of IPS and few commercial solutions exist. Integration into Smart Homes could allow for secondary services including location-based services, targeted user experiences and intrusion detection, to be enabled using the existing underlying infrastructure. Since New Zealand has an aging population, we must ensure that the elderly are well looked after. An IPS solution could detect whether a person has been immobile for an extended period and alert medical personnel. A major shortcoming of existing IPS is their reliance on end-users to undertake a significant infrastructure investment to facilitate the localization tasks. An IPS that does not require extensive installation and calibration procedures, could potentially see significant uptake from end users. In order to expedite the widespread adoption of IPS technology, this thesis focuses on four major areas of improvement, namely: infrastructure reuse, reduced node density, algorithm improvement and reduced end user calibration requirements. The work presented demonstrates the feasibility of utilizing existing wireless and lighting infrastructure for positioning and implements novel spring-relaxation and potential fields-based localization approaches that allow for robust target tracking, with minimal calibration requirements. The developed novel localization algorithms are benchmarked against the existing state of the art and show superior performance.
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    Non-RSSI based energy efficient transmission power control protocol for low power indoor wireless sensor networks : a thesis presented in partial fulfilment of the requirements for the degree of PhD in Engineering at Massey University, Palmerston North, New Zealand
    (Massey University, 2016) Basu, Debraj
    In this thesis, we present the state-based adaptive power control (S-APC) protocol that is aimed to reduce energy consumption in low power wireless sensors while maintaining an application specific packet success rate requirement. The state-based approach is unique of its kind that dynamically adapt to the varying path losses caused by the movement of mobile sensors, by obstructions appearing between the stationary sensor and the base-station and movements of objects or humans in between two communicating stations. Since the primary reason for a drop in transmitted packets is the poor signal-to-noise ratio, it is important for the sensor to select a set of RF transmission power levels that will deliver the packets within a specified error rate while using the least amount of energy. In a battery-powered wireless sensor node, the use of ARQ (Automatic Repeat reQuest) protocol will lead to retransmissions when an attempt to send a packet fails. The proposed adaptive protocol does not use received signal strength indication (RSSI) based beacon or probe packets nor does it listen to the channel before transmitting for channel estimation. The use of the proposed S-APC protocol is not limited to only sensor network. It is applicable to any kind of radio communication when the transmitting radio frequency (RF) modules have configurable output power and options for retransmission. This proposed protocol can comfortably work on top of existing MAC protocol that is contention based and listens to channel before transmitting. The hardware used for evaluating the protocol parameters is the nRF24L01p transceiver module from Nordic Semiconductor Inc. This radio module is cheaper than other modules that provide the RSSI values to the chip and the application of the adaptive power control protocol can further reduce the overall deployment and running cost of a sensor network. The proposed protocol is designed to respond to an unknown and variable radio channel in an energy-efficient manner. The adaptive protocol uses past transmission experience or memory to decide the power level at which the new packet transmission will start. It also uses a drop-off algorithm to ramp down power level as and when required. Simulation has been used to compare the performance with the existing RSSI and non-RSSI based adaptive power control protocol. Results have shown that when the channel condition is between average and poor (ratio of bit energy (Eb) and noise power spectral density (N0) is less than 20 dB), the RSSI based adaptive protocol consumes 10-20% more energy. Following the simulations, exhaustive experimental trials were done to compare S-APC with the existing protocols. It was found that there can be an increase of energy efficiency up-to 33% over fixed power transmission. This protocol could be applied in mobile robots that collect data in real time from sensors and transmit to the base station as well as to body wearable sensors used for monitoring the health conditions of patients in a health facility centre. Overall, this adaptive protocol can be used in radio communication where the channel has dynamic temporal and spatial characteristics to enhance the lifetime of battery powered wireless sensors.
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    Real-time fusion of wireless sensor network data for wellness determination of the elderly in a smart home : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Computer Science and Engineering at Massey University, Manawatu, New Zealand
    (Massey University, 2014) Suryadevara, Nagender Kumar
    In this research, I have explored a methodology for the development of efficient electronic real time data processing system to recognize the behaviour of an elderly person. The ability to determine the wellness of an elderly person living alone in their own home using a robust, flexible and data driven artificially intelligent system has been investigated. A framework integrating temporal and spatial contextual information for determining the wellness of an elderly person has been modelled. A novel behaviour detection process based on the observed sensor data in performing essential daily activities has been designed and developed. The model can update the behaviour knowledge base and simultaneously execute the tasks to explore the intricacies of the generated behaviour pattern. An initial decline or change in regular daily activities can suggest changes to the health and functional abilities of the elderly person. The developed system is used to forecast the behaviour and quantitative wellness of the elderly by monitoring the daily usages of household appliances using smart sensors. Wellness determination models are tested at various elderly houses, and the experimental results related to the identification of daily activities and wellness determinations are encouraging. The wellness models are updated based on the time series analysis formulations. The integrated smart sensing system is capable of detecting human emotion and behaviour recognition based on the daily functional abilities simultaneously. The electronic data processing system can incorporate the Internet of Things framework for sensing different devices, understand and act according to the requirement of smart home environment.
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    Modelling and performance study of large scale Zigbee based green house monitoring and control network : a thesis presented in partial fulfillment of the requirements for the degree of Master of Engineering in Electronics and Communication Engineering at Massey University, Albany, New Zealand
    (Massey University, 2013) Hoque, Iftekharul
    Zigbee wireless sensor networks, known as IEEE 802.15.4 standard, have become quite popular in recent years due to its low power consumption, long battery life and security management. Academic and networking industries have taken interest in Zigbee (IEEE 802.15.4) due to its capability for multiple applications. In this thesis, we have studied Zigbee wireless sensor networks in geographically distributed greenhouses, which are a vital component in agriculture industry today. However due to the complexity and scattered nature of the proposed large scaled network, we only simulate the scenarios in an industry standard and powerful simulator called OPNET to achieve the perfect design and high percentage success. We investigate the performance parameters such as throughput, end-to-end delay, packet loss, traffic sent and traffic received depending on the network topology under various layouts and node conditions based on specific features and recommendations of the IEEE 802.15.4/ZigBee standards. Since the network delay is the most important characteristic, we investigate this parameter first. We find that the delay increases as the number of greenhouses increases e.g. the delay for 20- greenhouse (GH) scenario is higher than 50- GH scenario. This is contrary to generally perceived understanding however our initial delay was also greater for 50- GH scenario but later due to many un-joined nodes, the delay fell suddenly. The next parameter we investigate is MAC throughput which is seen as increasing when there is communication between maximum nodes. The 20- GHs scenario is shows maximum MAC throughput whereas the scenario with 50- GHs stays way below 20- GHs. We also observe that the number of packets drops significantly in case of 50- GHs. This is attributed to the possibly of the routers dropping the joining or relay requests from end devices while they are too busy in processing requests from other end devices. We can conclude from the above that if the setup is as big as 50 GHs, we can’t rely on single coordinator setup as it is too far for the nodes to hop all the way. On the other hand, the traffic sent in scenario with 20- GH reaches the IEEE 802.15.4 industry specification of 250 kbps showing that the data is being sent at maximum possible rates in this scenario. So, real life implementation of this setup is possible for small number of GHs like 20- GHs. The scenario with 20- GHs and nodes spaced at 20 m has shown favorable results for all the parameters such as throughput, delay and traffic even for a single coordinator. Though our simulations worked and have been able to get reasonable results there are many challenges that need be met to improve the outcome of this as well as any other study involving simulation of the geographically dispersed very large scale Zigbee-based wireless sensor networks. Another challenge in this design is that the simulation of 50- GH with nodes close to 1000 takes large amount of time execute. Nonetheless, based on the findings from this work, it will be helpful to design the GH/nodes layout of the implementation in OPNET. The most important achievement of the work is that we have been able to develop a simulation model for the geographically dispersed very large scale Zigbee-based wireless sensor network representing networked greenhouses. Considering the results of throughput, end-to-end delay, packet loss, traffic sent and traffic received it looks the network can support optimally a 20- GH setup for remote monitoring and control application.
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    Design and implementation of Internet of Things for home environment : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Electronics and Computer Systems Engineering at Massey University, Manawatu, New Zealand
    (Massey University, 2013) Kelly, Sean
    An integrated framework for smart home monitoring towards internet of things based on ZigBee and 6LoWPAN wireless sensor networks is presented. The system was developed to retrofit existing sub systems of wireless technologies in order to reduce cost, and complexity. The practical internetworking architecture and the connection procedures for reliable measurement of smart sensors parameters and transmission of sensing data via internet are presented. A ZigBee based sensing system was designed and developed to see the feasibility of the system in home automation for contextual environmental monitoring. The ubiquitous sensing system is based on combination of pervasive distributed sensing units and an information system for data aggregation and analysis. Results related to the home automation parameters and execution of the system running continuously for long durations is encouraging. The prototype system (ZigBee based) was tested to generate real-time graphical information rather than using a simulator or a test bed scenario. A trail has also been performed with 6LoWPAN technology to provide functionality as the ZigBee based system. The overall internetworking architecture describes the integration of a low power consumption wireless sensor network with the internet. The proposed prototype has advantages in terms of low cost, flexibility of usage. The design of the integrated framework provides a template for other applications related to the Internet of Things.
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    Smart power monitoring utility system using wireless sensor networks : a project report submitted in partial fulfilment of the requirements for the degree of Master of Engineering in Electronics and Electrical Engineering
    (Massey University, 2013) Gill, Satinder Pal Singh
    The design and development of a Wireless Sensor Networks based Smart Grid for home utility system for power utility has been presented in this thesis. The system utilises wireless power monitoring devices and control units. The electronic wireless power monitoring devices have been designed to monitor electrical parameters such as voltage, current and power of the household appliances. The measured electrical parameters are transmitted to a central controller via the ZigBee node. The central coordinator has been configured around a laptop computer and receives all the transmitted data from different nodes. The computer stores the measured data and analyses them. The computer is also connected to internet and the website of the electrical power supply company is accessed. The real-time electricity tariff is available to the controller. Based on the tariff condition the controller can determine the off-peak and peak-electricity rate. The controller can decide to switch off the unimportant electrical loads at peak-tariff situation. This is implemented by sending the necessary command to the zigbee node connected to the appropriate load. The zigbee node can then switch off the load by sending an off-command to the triac which is used as the control device. The user has the options of controlling the electrical appliances in different modes. If the users would like to continue the load to be on during the peak-tariff condition, the option of a manual switch can be used to bypass the triac. The appropriate electrical loads can be monitored as well as controlled using the developed GUI available at the laptop. The complete information of the system is also available through a website and appropriate control action can be implemented through a secured access. The objective of the research is to lower the consumption of power during the peak-tariff condition and thereby saves electricity cost. A prototype has been designed, developed and extensively tested. This Thesis presents the current work, experimental results and concludes with possible future research opportunities.
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    A cross layer opportunistic routing protocol for wireless sensor network : analysis, modelling and quality of service support : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Communication and Network Engineering at Massey University, Manawatu, New Zealand
    (Massey University, 2013) Rusli, Mohd Ezanee
    A wireless sensor network (WSN) provides a platform for embedded sensing and ubiquitous computing. For ad hoc WSNs, multi-hop routing has been adopted in order to save communication power consumption. By acknowledging the lossy characteristics of radio channels on low-power WSNs, the Opportunistic Routing (OR) protocol provides an efficient method for exploiting the spatial and temporal characteristics of these wireless networks by considering multiple forwarding relays for each transmission. The main contribution of this thesis is to provide analysis and modelling for variants of the OR protocol for WSNs. Firstly, based on the basic concepts that underpin OR, we propose a new variant of OR that can be used in WSNs. It is known that communication in WSN is the most power consuming operation; hence, we propose a variant of OR that specifically reduces the total number of transmissions required during the coordination step used in OR. We investigate the effectiveness of this approach and compare it with OR that adopts existing and common candidate coordination schemes. In addition, we also propose a retransmission scheme based on provisional reliability constraints for local loss recovery that can be used in this new variant of OR. Secondly, we propose a comprehensive new analytical framework that is based on Markov Chain and Queueing theories that takes into account the key component strategies of OR (prioritization, selection and coordination) as well as the communication components of WSN. The proposed framework can be used to model the end-to-end reliability and delay performances of WSNs using OR. Thirdly, taking into account the potential deficiencies of OR due to its static coordination scheme, we introduce a variant of OR that is aware of the online quality of its selected forwarding relays that we have named as the Adaptive Coordination Opportunistic Routing (ACOR) protocol. We propose a new local metric to be known as the Opportunistic Quality Score for ACOR to improve the performance of WSNs and, in particular, to support Quality of Service delivery of messages in these networks. In addition, we provide an analytical framework for ACOR that incorporates the adaptive coordination scheme that has been developed.
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    A WiFi based smart wireless sensor network for an agricultural environment : a thesis submitted in fulfilment of the requirements for the degree of Master of Engineering
    (Massey University, 2012) Mendez, Gerard Rudolph
    Environmental Monitoring Systems and Sensors systems have increased in importance over the years. However, increases in measurement points mean increases in installation and maintenance cost. Not to mention, the measurement points once they have been built and installed, can be tedious to relocate in the future. Therefore, the purpose of this Masters thesis is to present a project called “A Wi-Fi based Smart Wireless Sensor Network for an Agricultural Environment” which is capable of intelligently monitoring agricultural conditions in a pre-programmed manner. The proposed system consists of three stations: Sensor Node, Router, and Server. To allow for better monitoring of the climate condition in an agricultural environment such as field or greenhouse, the sensor station is equipped with several sensor elements such as Temperature, humidity, light, air pressure, soil moisture and water level. In addition investigation was performed in order to integrate a novel planar electromagnetic sensor for nitrate detection. The communication between the sensor node and the server is achieved via 802.11g wireless modules. The overall system architecture shows advantages in cost, size, flexibility and power. It is believed that the outcomes of the project allow for opportunities to perform further research and development of a Wi-Fi based Wireless Sensor Network that is a portable and flexible type of sensing system for an Agricultural Environment.