Tracking mobile targets through Wireless Sensor Networks

In recent years, advances in signal processing have led to small, low power, inexpensive Wireless Sensor Network (WSN). The signal processing in WSN is different from the traditional wireless networks in two critical aspects: firstly, the signal processing in WSN is performed in a fully distributed manner, unlike in traditional wireless networks; secondly, due to the limited computation capabilities of sensor networks, it is essential to develop an energy and bandwidth efficient signal processing algorithms. Target localisation and tracking problems in WSNs have received considerable attention recently, driven by the necessity to achieve higher localisation accuracy, lower cost, and the smallest form factor. Received Signal Strength (RSS) based localisation techniques are at the forefront of tracking research applications. Since tracking algorithms have been attracting research and development attention recently, prolific literature and a wide range of proposed approaches regarding the topic have emerged. This thesis is devoted to discussing the existing WSN-based localisation and tracking approaches. This thesis includes five studies. The first study leads to the design and implementation of a triangulation-based localisation approach using RSS technique for indoor tracking applications. The presented work achieves low localisation error in complex environments by predicting the environmental characteristics among beacon nodes. The second study concentrates on investigating a fingerprinting localisation method for indoor tracking applications. The proposed approach offers reasonable localisation accuracy while requiring a short period of offline computation time. The third study focuses on designing and implementing a decentralised tracking approach for tracking multiple mobile targets with low resource requirements. Despite the interest in target tracking and localisation issues, there are few systems deployed using ZigBee network standard, and no tracking system has used the full features of the ZigBee network standard. Tracking through the ZigBee is a challenging task when the density of router and end-device nodes is low, due to the limited communication capabilities of end-device nodes. The fourth study focuses on developing and designing a practical ZigBee-based tracking approach. To save energy, different strategies were adopted. The fifth study outlines designing and implementing an energy-efficient approach for tracking applications. This study consists of two main approaches: a data aggregation approach, proposed and implemented in order to reduce the total number of messages transmitted over the network; and a prediction approach, deployed to increase the lifetime of the WSN. For evaluation purposes, two environmental models were used in this thesis: firstly, real experiments, in which the proposed approaches were implemented on real sensor nodes, to test the validity for the proposed approaches; secondly, simulation experiments, in which NS-2 was used to evaluate the power-consumption issues of the two approaches proposed in this thesis

Implementation of signal conditioning circuitry for CO2 sensor for monitoring CO2 emissions from coal fired power plant in Neyveli Lignite Corporation (Tamil Nadu, India)

The most significant anthropogenic greenhouse gas causing global warming is carbon dioxide (CO2). Due to the increase of burning of fossil fuels by industries, the atmospheric CO2 concentration increased by more than 30% in 10 years and is expected to continue to increase. This dissertation analyses a sensor unit used to monitor the emission levels of carbon dioxide from the Neyveli Lignite Corporation (NLC) coal fired power plant which is located in the southern part of India. Most of India’s power generation sectors are based on coal fired power plants. The NLC power plant is owned by the central government of India. It can produce a maximum electric power of 2490MW. The power plant lets out significant CO2 emissions while generating electricity. These carbon dioxide emissions are the root cause for the greenhouse effect. To control the carbon dioxide emissions, in this dissertation a sensor has been designed, analysed and used to monitor the CO2 emission levels from the Neyveli Lignite Corporation. This dissertation focuses on the design and implementation of the CO2 sensor using various electronic components. In NLC, this CO2 sensor was kept under observation and tested. The CO2 emissions measured by the sensor were analysed to monitor CO2 emissions from the Neyveli Lignite Corporation and to guide measures and policy for future scenarios. This dissertation identifies and examines the CO2 emission levels and the possible environmental impacts. It also describes the advantages/disadvantages of the CO2 sensor and how this could guide the possible reduction of greenhouse gases (GHGs) to meet a green environment agenda in the future. Key environmental concerns in the coal-power sector in India include air pollution (primarily from the flue gas emissions of particulates, carbon dioxide emissions, sulphur oxides, nitrous and other hazardous chemicals) which has led to increased particulate pollution and ash disposal problems. The enforcement of regulations to reduce CO2 emissions has been weak in the southern part of India

Proximity-based systems: Incorporating mobility and scalability through proximity sensing

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This thesis argues that the concept of spatial proximity offers a viable and practical option for the development of context-aware systems for highly mobile and dynamic environments. Such systems would overcome the shortcomings experienced by today’s location-based and infrastructure dependent systems whose ability to deliver context-awareness is prescribed by their infrastructure. The proposed architecture will also allow for scalable interaction as against the single level of interaction in existing systems which limits services to a particular sized area. The thesis examines the concept of spatial proximity and demonstrates how this concept can be exploited to take advantage of technological convergence to offer mobility and scalability to systems. It discusses the design of a proximity-based system that can deliver scalable context-aware services in highly mobile and dynamic environments. It explores the practical application of this novel design in a proximity-sensitive messaging application by creating a proof-of-concept prototype. The proof-of-concept prototype is used to evaluate the design as well as to elicit user views and expectations about a proximity-based approach. Together these provide a valuable insight into the applicability of the proximity-based approach for designing context-aware systems. The design and development work discussed in the thesis presents a Proximity-Sensitive System Architecture that can be adapted for a variety of proximity-sensitive services. This is illustrated by means of examples, including a variety of context-aware messaging applications. The thesis also raises issues for information delivery, resource sharing, and human-computer interaction. While the technological solution (proximity-based messaging) offered is only one among several that can be developed using this architecture, it offers the opportunity to stimulate ideas in the relatively new field of proximity and technological convergence research, and contributes to a better understanding of their potential role in offering context-aware services

Sensors Utilisation and Data Collection of Underground Mining

This study reviews IMU significance and performance for underground mine drone localisation. This research has designed a Kalman filter which extracts reliable information from raw data. Kalman filter for INS combines different measurements considering estimated errors to produce a trajectory including time, position and attitude. To evaluate the feasibility of the proposed method, a prototype has been designed and evaluated. Experimental results indicate that the designed Kalman filter estimates the internal states of a system

Integrating Smart Ceiling Fans and Communicating Thermostats to Provide Energy-Efficient Comfort

The project goal was to identify and test the integration of smart ceiling fans and communicating thermostats. These highly efficient ceiling fans use as much power as an LED light bulb and have onboard temperature and occupancy sensors for automatic operationbased on space conditions. The Center for the Environment (CBE) at UC Berkeley led the research team including TRC, Association for Energy Affordability (AEA), and Big Ass Fans (BAF). The research team conducted laboratory tests, installed99 ceiling fans and 12 thermostats in four affordable multifamily housing sites in California’s Central Valley, interviewed stakeholders to develop a case study, developed an online design tool and design guide, outlined codes and standards outreach, and published several papers.The project team raised indoor cooling temperature setpoints and used ceiling fans as the first stage of cooling; this sequencing of ceiling fans and air conditioningreducesenergy consumption, especially during peak periods, while providing thermal comfort.The field demonstration resulted in 39% measured compressor energy savings during the April–October cooling seasoncompared to baseline conditions, normalized for floor area. Weather-normalized energy use varied from a 36% increase to 71% savings, withmedian savings of 15%.This variability reflects the diversity in buildings, mechanical systems, prior operation settings, space types, andoccupants’ schedules,preferences, and motivations. All commercial spaces with regular occupancy schedules (and twoof the irregularly-occupied commercial spaces and one of the homes) showed energy savings on an absolute basis before normalizing for warmer intervention temperatures,and 10 of 13 sites showed energy savings on a weather-normalized basis. The ceiling fans provided cooling for one site for months during hot weather when the coolingequipment failed.Occupants reported high satisfaction with the ceiling fans and improved thermal comfort. This technology can apply to new and retrofit residential and commercial buildings

Integrated Satellite-terrestrial networks for IoT: LoRaWAN as a Flying Gateway

When the Internet of Things (IoT) was introduced, it causes an immense change in human life. Recently, different IoT emerging use cases, which will involve an even higher number of connected devices aimed at collecting and sending data with different purposes and over different application scenarios, such as smart city, smart factory, and smart agriculture. In some cases, the terrestrial infrastructure is not enough to guarantee the typical performance indicators due to its design and intrinsic limitations. Coverage is an example, where the terrestrial infrastructure is not able to cover certain areas such as remote and rural areas. Flying technologies, such as communication satellites and Unmanned Aerial Vehicles (UAVs), can contribute to overcome the limitations of the terrestrial infrastructure, offering wider coverage, higher resilience and availability, and improving user\u2019s Quality of Experience (QoE). IoT can benefit from the UAVs and satellite integration in many ways, also beyond the coverage extension and the increase of the available bandwidth that these objects can offer. This thesis proposes the integration of both IoT and UAVs to guarantee the increased coverage in hard to reach and out of coverage areas. Its core focus addresses the development of the IoT flying gateway and data mule and testing both approaches to show their feasibility. The first approach for the integration of IoT and UAV results in the implementing of LoRa flying gateway with the aim of increasing the IoT communication protocols\u2019 coverage area to reach remote and rural areas. This flying gateway examines the feasibility for extending the coverage in a remote area and transmitting the data to the IoT cloud in real-time. Moreover, it considers the presence of a satellite between the gateway and the final destination for areas with no Internet connectivity and communication means such as WiFi, Ethernet, 4G, or LTE. The experimental results have shown that deploying a LoRa gateway on board a flying drone is an ideal option for the extension of the IoT network coverage in rural and remote areas. The second approach for the integration of the aforementioned technologies is the deployment of IoT data mule concept for LoRa networks. The difference here is the storage of the data on board of the gateway and not transmitting the data to the IoT cloud in real time. The aim of this approach is to receive the data from the LoRa sensors installed in a remote area, store them in the gateway up until this flying gateway is connected to the Internet. The experimental results have shown the feasibility of our flying data mule in terms of signal quality, data delivery, power consumption and gateway status. The third approach considers the security aspect in LoRa networks. The possible physical attacks that can be performed on any LoRa device can be performed once its location is revealed. Position estimation was carried out using one of the LoRa signal features: RSSI. The values of RSSI are fed to the Trilateration localization algorithm to estimate the device\u2019s position. Different outdoor tests were done with and without the drone, and the results have shown that RSSI is a low cost option for position estimation that can result in a slight error due to different environmental conditions that affect the signal quality. In conclusion, by adopting both IoT technology and UAV, this thesis advances the development of flying LoRa gateway and LoRa data mule for the aim of increasing the coverage of LoRa networks to reach rural and remote areas. Moreover, this research could be considered as the first step towards the development of high quality and performance LoRa flying gateway to be tested and used in massive LoRa IoT networks in rural and remote areas

A real-time data monitoring prototype protocol to advance environmental management through a citizen science approach– A case study in Nepal

The lack of environmental monitoring data has restricted the efficiency of proper environmental management in the developing world. Although monitoring technologies have been touted for their potential to advance environmental understanding and management, there are very few examples of practical applications where this has been accomplished in the developing world. Due to the positive influx of urbanization and tourism in Siddharthanagar, South Nepal, the Nepal Study Center (NSC) from the University of New Mexico (UNM) teamed up with the poly-tech college Pratiman-Neema Health Institute (PNMHI) to address future environmental changes through a citizen science approach, known as the Danda River Monitoring Program (DEMP). The objective of this professional project is to develop and deploy a prototype protocol for monitoring air, weather, and water in a location in Nepal where environmental data is not available. This professional project identifies and executes a practical framework strategy to initiate a wireless environmental sensor network to gain access to a long-term data collection plan through a citizen science approach. Citizen science is the participation of any citizen who interacts in a data collection and monitoring process. The scientific data gathered from the monitoring sensors, combined with curricular toolkits, will be used in a digital lab setting to educate students and community members to enhance their learning and environmental awareness. Assisting in the initial implementation process was impactful, for the wireless sensors are currently collecting data, a citizen science survey was successfully administered to understand future improvements, and a robust collaborative relationship between NSC and PNMHI was established. Furthermore, an enhancement of the capabilities of the community to learn and make firm data-driven decisions focused on human and environmental health was implemented. The value that this project brings to the community is fourfold: water resource management, health management, a platform for enhanced science studies, and an established program to attract eco-tourism that will, in turn, preserve the ecosystem and natural heritage of the community. Ultimately, the study found that the efforts performed to demonstrate a positive impact on the community in Nepal. This program has strong support from various stakeholders and the potential to improve the environment and health of the people in Nepal

A model personal energy meter

Every day each of us consumes a significant amount of energy, both directly through transport, heating and use of appliances, and indirectly from our needs for the production of food, manufacture of goods and provision of services. This dissertation investigates a personal energy meter which can record and apportion an individual's energy usage in order to supply baseline information and incentives for reducing our environmental impact. If the energy costs of large shared resources are split evenly without regard for individual consumption each person minimises his own losses by taking advantage of others. Context awareness offers the potential to change this balance and apportion energy costs to those who cause them to be incurred. This dissertation explores how sensor systems installed in many buildings today can be used to apportion energy consumption between users, including an evaluation of a range of strategies in a case study and elaboration of the overriding principles that are generally applicable. It also shows how second-order estimators combined with location data can provide a proxy for fine-grained sensing. A key ingredient for apportionment mechanisms is data on energy usage. This may come from metering devices or buildings directly, or from profiling devices and using secondary indicators to infer their power state. A mechanism for profiling devices to determine the energy costs of specific activities, particularly applicable to shared programmable devices is presented which can make this process simpler and more accurate. By combining crowdsourced building-inventory information and a simple building energy model it is possible to estimate an individual's energy use disaggregated by device class with very little direct sensing. Contextual information provides crucial cues for apportioning the use and energy costs of resources, and one of the most valuable sources from which to infer context is location. A key ingredient for a personal energy meter is a low cost, low infrastructure location system that can be deployed on a truly global scale. This dissertation presents a description and evaluation of the new concept of inquiry-free Bluetooth tracking that has the potential to offer indoor location information with significantly less infrastructure and calibration than other systems. Finally, a suitable architecture for a personal energy meter on a global scale is demonstrated using a mobile phone application to aggregate energy feeds based on the case studies and technologies developed