RFID Localisation For Internet Of Things Smart Homes: A Survey

The Internet of Things (IoT) enables numerous business opportunities in fields as diverse as e-health, smart cities, smart homes, among many others. The IoT incorporates multiple long-range, short-range, and personal area wireless networks and technologies into the designs of IoT applications. Localisation in indoor positioning systems plays an important role in the IoT. Location Based IoT applications range from tracking objects and people in real-time, assets management, agriculture, assisted monitoring technologies for healthcare, and smart homes, to name a few. Radio Frequency based systems for indoor positioning such as Radio Frequency Identification (RFID) is a key enabler technology for the IoT due to its costeffective, high readability rates, automatic identification and, importantly, its energy efficiency characteristic. This paper reviews the state-of-the-art RFID technologies in IoT Smart Homes applications. It presents several comparable studies of RFID based projects in smart homes and discusses the applications, techniques, algorithms, and challenges of adopting RFID technologies in IoT smart home systems.Comment: 18 pages, 2 figures, 3 table

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

Improved Indoor Location Systems in a Controlled Environments

The precise localization by using Wi-Fi Access Point (AP) has become a very important issue for indoor location based services such as marketing, patient follow up and so on. Present AP localization systems are working on specially designed Wi-Fi units, and their algorithms using radio signal strength (RSS) exhibit (relatively) high errors, so industry looks more precise and fast adaptable methods. A new model considering/eliminating strong RSS levels in addition to close distance error elimination algorithm (CDEEA) combined with median filters has been proposed in order to increase the performance of conventional RSS based location systems. Collecting local signal strengths by means of an ordinary WiFi units present on any laptop as a receiver is followed by the application of CDEEA to eliminate strong RSS levels. Median filter is then applied to those eliminated values, and AP based path loss model is generated, adaptivelly. Finally, the proposed algorithm predicts locations within a maximum mean error of 2.96m for 90% precision level. This achievement with an ordinary wifi units present on any commercial laptop is comparably at very good level in literature

Real-time localization using received signal strength

Locating and tracking assets in an indoor environment is a fundamental requirement for several applications which include for instance network enabled manufacturing. However, translating time of flight-based GPS technique for indoor solutions has proven very costly and inaccurate primarily due to the need for high resolution clocks and the non-availability of reliable line of sight condition between the transmitter and receiver. In this dissertation, localization and tracking of wireless devices using radio signal strength (RSS) measurements in an indoor environment is undertaken. This dissertation is presented in the form of five papers. The first two papers deal with localization and placement of receivers using a range-based method where the Friis transmission equation is used to relate the variation of the power with radial distance separation between the transmitter and receiver. The third paper introduces the cross correlation based localization methodology. Additionally, this paper also presents localization of passive RFID tags operating at 13.56MHz frequency or less by measuring the cross-correlation in multipath noise from the backscattered signals. The fourth paper extends the cross-correlation based localization algorithm to wireless devices operating at 2.4GHz by exploiting shadow fading cross-correlation. The final paper explores the placement of receivers in the target environment to ensure certain level of localization accuracy under cross-correlation based method. The effectiveness of our localization methodology is demonstrated experimentally by using IEEE 802.15.4 radios operating in fading noise rich environment such as an indoor mall and in a laboratory facility of Missouri University of Science and Technology. Analytical performance guarantees are also included for these methods in the dissertation --Abstract, page iv

Neighborhood Localization Method for Locating Construction Resources Based on RFID and BIM

Construction sites are changing every day, which brings some difficulties for different contractors to do their tasks properly. One of the key points for all entities who work on the same site is the location of resources including materials, tools, and equipment. Therefore, the lack of an integrated localization system leads to increase the time wasted on searching for resources. In this research, a localization method which does not need infrastructure is proposed to overcome this problem. Radio Frequency Identification (RFID) as a localization technology is integrated with Building Information Modeling (BIM) as a method of creating, sharing, exchanging and managing the building information throughout the lifecycle among all stakeholders. In the first stage, a requirements’ gathering and conceptual design are performed to add new entities, data types, and properties to the BIM, and relationships between RFID tags and building assets are identified. Secondly, it is proposed to distribute fixed tags with known positions as reference tags for the RFID localization approach. Then, a clustering method chooses the appropriate reference tags to provide them to an Artificial Neural Network (ANN) for further computations. Additionally, Virtual Reference Tags (VRTs) are added to the system to increase the resolution of localization while limiting the cost of the system deployment. Finally, different case studies and simulations are implemented and tested to explore the technical feasibility of the proposed approach

Recent Advances in Indoor Localization Systems and Technologies

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods

Improved back-of-the-house processes with RFID enabled it model for hospitality industry in Singapore

This is a research paper exploring the ability of Radio Frequency Identification (RFID) technology to cope with challenges of back-of-the-house of the hospitality industry in Singapore. Focused on supply chain, food safety and security, the paper reviewed the three integrated service support processes of back-of-the-house that drove the service delivery processes of front-of-the-house in meeting the critical reliability dimension of SERVQUAL model. The RFID mobile technology’s advantages were studied in mitigating risks and meeting compliances within the three back-of-the-house areas. The RFID was further examined as a viable IT solution based on the potential impacts associated with cost-of-not-doing and the improved ROI over cost-of-doing. Constructed by using service blueprinting technique, the RFID enabled IT model was proposed for real-time tracking and interfacing with systems and processes. The advantages of the model were illustrated to improve efficiency and enhance capability of back-of-the-house processes. Explaining the limitations of the model, the paper also recommended the five-step approach of RFID implementation and future research on lifecycle tracking benefits

Smart e-Health System for Real-time Tracking and Monitoring of Patients, Staff and Assets for Healthcare Decision Support in Saudi Arabia

Healthcare in Saudi Arabia has been lagging behind the developed countries of the world, due to the insufficient number of healthcare practitioners and the lack of applications of tracking and monitoring technology. These shortages have contributed to problems such as patient misidentification, long patient waiting times, and the inability to locate medical equipment efficiently. The country’s Vision 2030 plan outlines ways to solve the deficient workforce problem by promoting more local health-related educational outlets, and by funding this expanding sector. Consequently, Saudi Arabia needs to adapt to the demanding nature of modern healthcare, which presents major problems that this research aims to help solve. The literature has shown that Information Technology systems have begun to be implemented in some hospitals across Saudi Arabia, but even in those hospitals these technologies are being under-utilised. The intention of this thesis is to provide an appropriate choice for a real-time tracking and monitoring technology in healthcare, in the form of an integrated RFID/ZigBee system. This thesis develops a holistic framework for healthcare institutions, to be followed for customised solutions in improving staff efficiency and productivity, and for better patient care, while minimising long-term costs. This holistic framework incorporates contextual elements from both the Information System Strategy Triangle (ISST) and the Human, Organisation and Technology-fit factors (HOT-fit) frameworks, in a way that ensures the new framework addresses technology, organisational, human and business factors. The holistic model is refined through Communities of Practice (CoPs), one of which was developed and utilised for the research purposes of this thesis, and assisted in the creation of a questionnaire for assessing the requirements and challenges of the KSA healthcare system. This questionnaire was based on 220 usable responses. It also helped to refine the framework for its final version, which included all identified factors relevant to the decision a healthcare institution faces in choosing a health information technology system. Various cases were analysed to improve the hospitals workflow, using the proposed technology and including processes such as relocating staff and medical assets. This led to the need for visualisation and knowledge management, to support real-time data analysis for business intelligence decision making. The end goal of this analysis is to provide interactive platforms to healthcare staff for use in improving efficiency and productivity. The outcomes of these improvements will be to ensure better patient care, lower patient waiting time, reduced healthcare costs, and to allow more time for staff to provide improved patient-centric care in the Saudi healthcare sector. Keywords: e-Health, Health Information Technology, Tracking and Monitoring System, Kingdom of Saudi Arabia, Holistic Framework, Communities of Practice, Knowledge Management, Visualisation, KFM

INDOOR-WIRELESS LOCATION TECHNIQUES AND ALGORITHMS UTILIZING UHF RFID AND BLE TECHNOLOGIES

The work presented herein explores the ability of Ultra High Frequency Radio Frequency (UHF RF) devices, specifically (Radio Frequency Identification) RFID passive tags and Bluetooth Low Energy (BLE) to be used as tools to locate items of interest inside a building. Localization Systems based on these technologies are commercially available, but have failed to be widely adopted due to significant drawbacks in the accuracy and reliability of state of the art systems. It is the goal of this work to address that issue by identifying and potentially improving upon localization algorithms. The work presented here breaks the process of localization into distance estimations and trilateration algorithms to use those estimations to determine a 2D location. Distance estimations are the largest error source in trilateration. Several methods are proposed to improve speed and accuracy of measurements using additional information from frequency variations and phase angle information. Adding information from the characteristic signature of multipath signals allowed for a significant reduction in distance estimation error for both BLE and RFID which was quantified using neural network optimization techniques. The resulting error reduction algorithm was generalizable to completely new environments with very different multipath behavior and was a significant contribution of this work. Another significant contribution of this work is the experimental comparison of trilateration algorithms, which tested new and existing methods of trilateration for accuracy in a controlled environment using the same data sets. Several new or improved methods of triangulation are presented as well as traditional methods from the literature in the analysis. The Antenna Pattern Method represents a new way of compensating for the antenna radiation pattern and its potential impact on signal strength, which is also an important contribution of this effort. The performance of each algorithm for multiple types of inputs are compared and the resulting error matrix allows a potential system designer to select the best option given the particular system constraints