Location estimation in smart homes setting with RFID systems

Indoor localisation technologies are a core component of Smart Homes. Many applications within Smart Homes benefit from localisation technologies to determine the locations of things, objects and people. The tremendous characteristics of the Radio Frequency Identification (RFID) systems have become one of the enabler technologies in the Internet of Things (IOT) that connect objects and things wirelessly. RFID is a promising technology in indoor positioning that not only uniquely identifies entities but also locates affixed RFID tags on objects or subjects in stationary and real-time. The rapid advancement in RFID-based systems has sparked the interest of researchers in Smart Homes to employ RFID technologies and potentials to assist with optimising (non-) pervasive healthcare systems in automated homes. In this research localisation techniques and enabled positioning sensors are investigated. Passive RFID sensors are used to localise passive tags that are affixed to Smart Home objects and track the movement of individuals in stationary and real-time settings. In this study, we develop an affordable passive localisation platform using inexpensive passive RFID sensors. To fillful this aim, a passive localisation framework using minimum tracking resources (RFID sensors) has been designed. A localisation prototype and localisation application that examined the affixed RFID tag on objects to evaluate our proposed locaisation framework was then developed. Localising algorithms were utilised to achieve enhanced accuracy of localising one particular passive tag which that affixed to target objects. This thesis uses a general enough approach so that it could be applied more widely to other applications in addition to Health Smart Homes. A passive RFID localising framework is designed and developed through systematic procedures. A localising platform is built to test the proposed framework, along with developing a RFID tracking application using Java programming language and further data analysis in MATLAB. This project applies localisation procedures and evaluates them experimentally. The experimental study positively confirms that our proposed localisation framework is capable of enhancing the accuracy of the location of the tracked individual. The low-cost design uses only one passive RFID target tag, one RFID reader and three to four antennas

Experimental Characterisation of Body-Centric Radio Channels Using Wireless Sensors

PhDWireless sensors and their applications have become increasingly attractive for industry, building automation and energy control, paving the way for new applications of sensor networks which go well beyond traditional sensor applications. In recent years, there has been a rapid growth in the number of wireless devices operating in close proximity to the human body. Wearable sensor nodes are growing popular not only in our normal living lifestyle, but also within healthcare and military applications, where different radio units operating in/on/off body communicate pervasively. Expectations go beyond the research visions, towards deployment in real-world applications that would empower business processes and future business cases. Although theoretical and simulation models give initial results of the antenna behaviour and the radio channel performance of wireless body area network (WBAN) devices, empirical data from different set of measurements still form an essential part of the radio propagation models. Usually, measurements are performed in laboratory facilities which are equipped with bulky and expensive RF instrumentation within calibrated and controllable environments; thus, the acquired data has the highest possible reliability. However, there are still measurement uncertainties due to cables and connections and significant variations when designs are deployed and measured in real scenarios, such as hospitals wards, commercial buildings or even the battle field. Consequently, more flexible and less expensive measurement tools are required. In this sense, wireless sensor nodes offer not only easiness to deploy or flexibility, but also adaptability to different environments. In this thesis, custom-built wireless sensor nodes are used to characterise different on-body radio channels operating in the IEEE 802.15.4 communication standard at the 2.45 GHz ISM band. Measurement results are also compared with those from the conventional technique using a Vector Network Analyser. The wireless sensor nodes not only diminished the effect of semi-rigid or flexible coaxial cables (scattering or radiation) used with the Vector Network Analyser (VNA), but also provided a more realistic response of the radio link channel. The performance of the wireless sensors is presented over each of the 16 different channels present at the 2.45 GHz band. Additionally, custom-built wireless sensors are used to characterise and model the performance of different on-body radio links in dynamic environments, such as jogging, rowing, and cycling. The use of wireless sensors proves to be less obstructive and more flexible than traditional measurements using coaxial cables, VNA or signal generators. The statistical analysis of different WBAN channels highlighted important radio propagation features which can be used as sport classifiers models and motion detection. Moreover, specific on-body radio propagation channels are further explored, with the aim to recognize physiological features such as motion pattern, breathing activity and heartbeat. The time domain sample data is transformed to the frequency domain using a non-parametric FFT defined by the Welch’s periodogram. The Appendix-Section D explores other digital signal processing techniques which include spectrograms (STFT) and wavelet transforms (WT). Although a simple analysis is presented, strong DSP techniques proved to be good for signal de-noising and multi-resolution analysis. Finally, preliminary results are presented for indoor tracking using the RSS recorded by multiple wireless sensor nodes deployed in an indoor scenario. In contrast to outdoor environments, indoor scenarios are subject to a high level of multipath signals which are dependent on the indoor clutter. The presented algorithm is based on path loss analysis combined with spatial knowledge of each wireless sensor

Performance evaluation of real-time indoor positioning with active RFID and ZigBee-based WSN systems

This study measures the accuracy of two radio signal-based positioning methods to track targets in an indoor environment using radio frequency identification (RFID) and a wireless sensor network (WSN), the advantages and disadvantages of which are compared, analyzed, and discussed. We propose a specific configuration to perform measurements in a real environment using various positioning algorithms. The experimental results show that the number and the quality of the reference tags influence the accuracy of positioning when using RFID devices. Although WSN devices require fewer sensors, the unit price of sensors is comparatively high. In addition, adjusting the antenna angle achieves a stronger received signal strength indicator variation when using RFID devices. For WSN devices, the key is to avoid interference between sensors because it causes large errors when estimating the distance between 2 points. The proposed positioning methods are suitable for patrol systems, and can be employed to obtain security service personnel location data and confirm their patrol routes. This study adopts active RFID technology and nano real-time positioning WSN technology to test the indoor positioning accuracy of these technologies and related system construction issues. The findings provide a reference for future research on indoor positioning method selection

OSEM : occupant-specific energy monitoring.

Electricity has become prevalent in modern day lives. Almost all the comforts people enjoy today, like home heating and cooling, indoor and outdoor lighting, computers, home and office appliances, depend on electricity. Moreover, the demand for electricity is increasing across the globe. The increasing demand for electricity and the increased awareness about carbon footprints have raised interest in the implementation of energy efficiency measures. A feasible remedy to conserve energy is to provide energy consumption feedback. This approach has suggested the possibility of considerable reduction in the energy consumption, which is in the range of 3.8% to 12%. Currently, research is on-going to monitor energy consumption of individual appliances. However, various approaches studied so far are limited to group-level feedback. The limitation of this approach is that the occupant of a house/building is unaware of his/her energy consumption pattern and has no information regarding how his/her energy-related behavior is affecting the overall energy consumption of a house/building. Energy consumption of a house/building largely depends on the energy-related behavior of individual occupants. Therefore, research in the area of individualized energy-usage feedback is essential. The OSEM (Occupant-Specific Energy Monitoring) system presented in this work is capable of monitoring individualized energy usage. OSEM system uses the electromagnetic field (EMF) radiated by appliances as a signature for appliance identification. An EMF sensor was designed and fabricated to collect the EMF radiated by appliances. OSEM uses proximity sensing to confirm the energy-related activity. Once confirmed, this activity is attributed to the occupant who initiated it. Bluetooth Low Energy technology was used for proximity sensing. This OSEM system would provide a detailed energy consumption report of individual occupants, which would help the occupants understand their energy consumption patterns and in turn encourage them to undertake energy conservation measures

A Low-power, Reachable, Wearable and Intelligent IoT Device for Animal Activity Monitoring

Along with the proliferation of mobile devices and wireless signal coverage, IoT devices, such as smart wristbands for monitoring its owner’s activity or sleep patterns, get great popularity. Wearable technology in human life has become quite useful due to the information given (sleep hours, heart rate, etc). However, wearables for animals does not give information about behaviour directly: they collect raw data that is sent to a server where, after a post-processing step, the behaviour is known. In this work, we present a smart IoT device that classifies different animal behaviours from the information obtained from on-board sensors using an embedded neural network running in the device. This information is uploaded to a server through a wireless sensor network based on Zigbee communication. The architecture of the device allows an easy assembly in a reduced dimension wearable case. The firmware allows a modular functionality by activating or deactivating modules independently, which improve the power efficiency of the device. The power consumption has been analyzed, allowing the 1Ah battery to work the system during several days. A novel localization and distance estimation technique (for 802.15.4 networks) is presented to recover a lost device in Do˜nana National Park with unidirectional antennas and log-normalization distance estimation over RSSI.Junta de Andalucía P12-TIC-1300Ministerio de Economía y Competitividad TEC2016-77785-

Edge Artificial Intelligence for Real-Time Target Monitoring

The key enabling technology for the exponentially growing cellular communications sector is location-based services. The need for location-aware services has increased along with the number of wireless and mobile devices. Estimation problems, and particularly parameter estimation, have drawn a lot of interest because of its relevance and engineers' ongoing need for higher performance. As applications expanded, a lot of interest was generated in the accurate assessment of temporal and spatial properties. In the thesis, two different approaches to subject monitoring are thoroughly addressed. For military applications, medical tracking, industrial workers, and providing location-based services to the mobile user community, which is always growing, this kind of activity is crucial. In-depth consideration is given to the viability of applying the Angle of Arrival (AoA) and Receiver Signal Strength Indication (RSSI) localization algorithms in real-world situations. We presented two prospective systems, discussed them, and presented specific assessments and tests. These systems were put to the test in diverse contexts (e.g., indoor, outdoor, in water...). The findings showed the localization capability, but because of the low-cost antenna we employed, this method is only practical up to a distance of roughly 150 meters. Consequently, depending on the use-case, this method may or may not be advantageous. An estimation algorithm that enhances the performance of the AoA technique was implemented on an edge device. Another approach was also considered. Radar sensors have shown to be durable in inclement weather and bad lighting conditions. Frequency Modulated Continuous Wave (FMCW) radars are the most frequently employed among the several sorts of radar technologies for these kinds of applications. Actually, this is because they are low-cost and can simultaneously provide range and Doppler data. In comparison to pulse and Ultra Wide Band (UWB) radar sensors, they also need a lower sample rate and a lower peak to average ratio. The system employs a cutting-edge surveillance method based on widely available FMCW radar technology. The data processing approach is built on an ad hoc-chain of different blocks that transforms data, extract features, and make a classification decision before cancelling clutters and leakage using a frame subtraction technique, applying DL algorithms to Range-Doppler (RD) maps, and adding a peak to cluster assignment step before tracking targets. In conclusion, the FMCW radar and DL technique for the RD maps performed well together for indoor use-cases. The aforementioned tests used an edge device and Infineon Technologies' Position2Go FMCW radar tool-set

Antenas setoriais para sistemas de localização em redes de sensores sem fios

Doutoramento em Engenharia EletrotécnicaThis work investigates low cost localization systems (LS) based on received signal strength (RSS) and integrated with different types of antennas with main emphasis on sectorial antennas. The last few years have witnessed an outstanding growth in wireless sensor networks (WSN). Among its various possible applications, the localization field became a major area of research. The localization techniques based on RSS are characterized by simplicity and low cost of integration. The integration of LS based on RSS and sectorial antennas (SA) was proven to provide an effective solution for reducing the number of required nodes of the networks and allows the combination of several techniques, such as RSS and angle of arrival (AoA). This PhD thesis focuses on studying techniques, antennas and protocols that best meet the needs of each LS with main focus on low cost systems based on RSS and AoA. Firstly there are studied localization techniques and system that best suit the requirements of the user and the antennas that are most appropriate according to the nature of the signal. In this step it is intended to provide a fundamental understanding of the undertaken work. Then the developed antennas are presented according to the following categories: sectorial and microstrip antennas. Two sectorial antennas are presented: a narrowband antenna operating at 2.4 to 2.5 GHz and a broadband antenna operating at 800MHz-2.4GHz. The low cost printed antennas were designed to operate at 5 GHz, which may be used for vehicular communication. After presenting the various antennas, several prototypes of indoor/outdoor LS are implemented and analyzed. Localization protocols are also proposed, one based on simplicity and low power, and the other on interoperability with different types of antennas and system requirements.O presente trabalho investiga sistemas de localização (SL) de baixo custo baseados na intensidade do sinal (RSS) e integrados com diferentes tipos de antenas com principal destaque para antenas sectoriais. Os últimos anos testemunharam um crescimento surpreendente de redes de sensores sem fios (RSSF), onde entre diversas aplicações possíveis, a localização tornou-se uma das principais áreas de pesquisa. Técnicas baseadas na intensidade do sinal caracterizam-se pela simplicidade e baixo custo de integração. A integração de SL baseados na intensidade do sinal recebido e antenas sectoriais (AS) oferecem uma solução eficaz para reduzir o número de nós necessários e para combinar diversas técnicas de localização. Esta tese de doutoramento foca-se no estudado de técnicas, antenas e protocolos de acordo com os requisitos de cada sistema localização com especial atenção para sistemas de baixo custo baseados na intensidade do sinal e no ângulo de chegada. Inicialmente são estudadas técnicas e SL de acordo com as necessidades do utilizador e as antenas que melhor se enquadram de acordo com a natureza do sinal. Esta etapa tem como objectivo proporcionar a compreensão fundamental do trabalho desenvolvido. Em seguida são apresentadas as antenas desenvolvidas divididas em: antenas sectorias e antenas impressas de baixo custo. Duas antenas sectoriais são apresentadas: uma de banda estreita a operar a 2,4-2,5GHz e outro de banda larga 800MHz-2.4GHz. As antenas impressas foram desenvolvidas para operar a 5 GHz, pelo que podem ser utilizadas para comunicação veicular. Após apresentação das diversas antenas vários protótipos de SL interiores/exteriores são implementados e analisados. Protocolos de localização são também propostos, um baseado na simplicidade e baixo consumo, outro na interoperabilidade com diferentes tipos de antenas e requisitos do sistema