Smart Geographic object: Toward a new understanding of GIS Technology in Ubiquitous Computing

One of the fundamental aspects of ubiquitous computing is the instrumentation of the real world by smart devices. This instrumentation constitutes an opportunity to rethink the interactions between human beings and their environment on the one hand, and between the components of this environment on the other. In this paper we discuss what this understanding of ubiquitous computing can bring to geographic science and particularly to GIS technology. Our main idea is the instrumentation of the geographic environment through the instrumentation of geographic objects composing it. And then investigate how this instrumentation can meet the current limitations of GIS technology, and offers a new stage of rapprochement between the earth and its abstraction. As result, the current research work proposes a new concept we named Smart Geographic Object SGO. The latter is a convergence point between the smart objects and geographic objects, two concepts appertaining respectively to

Embedded Dual Band Rfid Based Blood Glucose Monitoring System For Internet Of Medical Things

Manually recorded health information could lead to errors such as inaccurate patient identification and mismatch patient data that could seriously affect patient safety. In order to reduce the risks of error for patients with diabetes, a new design of wireless blood glucose monitoring system with the embedment of dual band RFID for Internet of Medical Things is being developed. Using this method, passive RFID allows short-range communication to read automatically the patient identification number and active RFID extends long-range communication for recording and monitoring blood glucose data through multi-hop WSN. The work presented in this thesis contributes mainly to the embedded system and its application in healthcare to reduce the burden of recording, tracing and monitoring the patient‘s data by embedding blood glucose sensor, passive RFID, active RFID, WSN, M2M and IoMT into a single platform. A new design concept is established for the patient identification mechanism, where the mechanism is embedded in the source device to enhance the ability of the system to automatically assign the identification number to each blood glucose measurement (mmol/L) during multiple patients monitoring. Additionally, the results from the experiments conducted showed that the developed system produced better overall performance compared to the Bluetooth BGM and conventional BGM system in terms of the shortest recording time and the ability to retransmit data. In the reliability analysis using ANOVA and DOE statistical methods, the result validates that the number of hop and number of end node significantly affects the PDR performance of conventional CSMA/CA. These two parameters are then taken into account in experimental setup for performance evaluation of the enhanced CSMA/CA (EN-CSMA/CA) algorithm that uses an external interrupt mechanism and a cross layer approach. The PDR increased from 94% (conventional CSMA/CA) to 99.33% (EN-CSMA/CA), an improvement of 5.33%. The PDR model estimates that for the best and worst scenario, the percentage of PDR is 100.0% and 51.67%, respectively. To optimize the arrangement of routers for real implementation of the developed system in health facilities, the developed path loss model estimates that the router should be positioned at a distance of 30 m from each other, which agrees with the test results which indicate that the router should be positioned ≤ 40 m in order to achieve the best PDR performance

Addressing data accuracy and information integrity in mHealth using ML

The aim of the study was finding a way in which Machine Learning can be applied in mHealth Solutions to detect inaccurate data that can potentially harm patients. The result was an algorithm that classified accurate and inaccurate data

Physiological and behavior monitoring systems for smart healthcare environments: a review

Healthcare optimization has become increasingly important in the current era, where numerous challenges are posed by population ageing phenomena and the demand for higher quality of the healthcare services. The implementation of Internet of Things (IoT) in the healthcare ecosystem has been one of the best solutions to address these challenges and therefore to prevent and diagnose possible health impairments in people. The remote monitoring of environmental parameters and how they can cause or mediate any disease, and the monitoring of human daily activities and physiological parameters are among the vast applications of IoT in healthcare, which has brought extensive attention of academia and industry. Assisted and smart tailored environments are possible with the implementation of such technologies that bring personal healthcare to any individual, while living in their preferred environments. In this paper we address several requirements for the development of such environments, namely the deployment of physiological signs monitoring systems, daily activity recognition techniques, as well as indoor air quality monitoring solutions. The machine learning methods that are most used in the literature for activity recognition and body motion analysis are also referred. Furthermore, the importance of physical and cognitive training of the elderly population through the implementation of exergames and immersive environments is also addressedinfo:eu-repo/semantics/publishedVersio

Consumers' perceptions of item-level RFID Use in FMCG: A balanced perspective of benefits and risks

This research explores how perceived consumer benefits affect the perceived privacy risks from implementation of Radio Frequency Identification (RFID) tags at an item-level in the Fast Moving Consumer Goods (FMCG) industry. Two new categories measure the benefits and risks: in-store and after-sales. These specific categories allow the respondents' willingness to accept RFID to be evaluated using a quantitative survey focused on the primary household grocery purchasers within the USA. The results suggest differences in perceptions of the in-store and after-sales risks and benefits of RFID use. While consumers are aware of privacy risks while using RFID technology, they would be willing to use the technology if sufficient benefits are available. This research moves the discussion away from a focus on consumer privacy issues to a balanced privacy/benefits approach for consumers and how that might affect their technology acceptance, suggesting that careful management of consumer benefits might allow FMCG firms to introduce RFID technology to support their global supply chains

Forder Application

Dissertação de Mestrado em Engenharia InformáticaIn Portugal eating out is a part of the lifestyle. People meet in coffee shops and restaurants, creating business opportunities for the owners of the places. In the summer season there are many bars that open their terrace service. Like many business, there are some ‘quiet times’ during the day – moments, when the place doesn’t receive so many clients. This project proposes an idea on how to maintain the efficiency of the outdoor service with possibly lower costs for the company. The application presented in the given project enables clients to make their requests directly from the table using a cellphone. In the next step the employee receives a notification with the request and he can prepare and deliver the order. Combining Proximity Communication Technologies and a web and mobile application, the communication between a client and an employee may turn out to be fast and comfortable. This solution can have an impact on the number of employees during a calmer time. It is also expected that the client will be able to receive his order in the faster way, through the implemented innovation

Battery-less near field communications (nfc) sensors for internet of things (iot) applications

L’ implementació de la tecnologia de comunicació de camp proper (NFC) en els telèfons intel·ligents no para de créixer degut a l’ús d’aquesta per fer pagaments, això, junt amb el fet de poder aprofitar l’energia generada pel mòbil no només per la comunicació, sinó també per transmetre energia, el baix cost dels xips NFC, i el fet de que els telèfons tinguin connectivitat amb internet, possibilita i fa molt interesant el disseny d’etiquetes sense bateria incorporant-hi sensors i poder enviar la informació al núvol, dins del creixent escenari de l’internet de les coses (IoT). La present Tesi estudia la viabilitat d’aquests sensors, analitzant la màxima distància entre lector i sensor per proveir la potència necessària, presenta tècniques per augmentar el rang d’operació, i analitza els efectes de certs materials quan aquests estan propers a les antenes. Diversos sensors han estat dissenyats i analitzats i son presentats en aquest treball. Aquests son: Una etiqueta que mesura la humitat de la terra, la temperatura i la humitat relativa de l’aire per controlar les condicions de plantes. Un sensor per detectar la humitat en bolquers, imprès en material flexible que s’adapta a la forma del bolquer. Dues aplicacions, una per estimació de pH i una altre per avaluar el grau de maduració de fruites, basats en un sensor de color. I, per últim, s’estudia la viabilitat de sensors en implants per aplicacions mèdiques, analitzant l’efecte del cos i proposant un sistema per augmentar la profunditat a la que aquests es poden llegir utilitzant un telèfon mòbil. Tots aquests sensors poden ser alimentats i llegits per qualsevol dispositiu que disposin de connexió NFC.La implementación de la tecnología de comunicaciones de campo cercano (NFC) en los teléfonos inteligentes no para de crecer debido al uso de esta para llevar a cabo pagos, esto, junto con el hecho de poder aprovechar la energía generada por el móvil no sólo para la comunicación, sino también para transmitir energía, el bajo coste de los chips NFC, i el hecho que los teléfonos tengan conectividad a internet, posibilita y hace muy interesante el diseño de etiquetas sin batería que incorporen sensores i poder enviar la información a la nube, enmarcado en el creciente escenario del internet de las cosas (IoT). La presente Tesis estudia la viabilidad de estos sensores, analizando la máxima distancia entre lector i sensor para proveer la potencia necesaria, presenta técnicas para aumentar el rango de operación, y analiza los efectos de ciertos materiales cuando estos están cerca de las antenas. Varios sensores han sido diseñados y analizados y son presentados en este trabajo. Estos son: Una etiqueta que mide la humedad de la tierra, la temperatura y la humedad relativa del aire para controlar las condiciones de plantas. Un sensor para detectar la humedad en pañales, impreso en material flexible que se adapta a la forma del pañal. Dos aplicaciones, una para estimación de pH y otra para evaluar el grado de maduración de frutas, basados en un sensor de color. Y, por último, se estudia la viabilidad de sensores en implantes para aplicaciones médicas, analizando el efecto del cuerpo y proponiendo un sistema para aumentar la profundidad a la que estos se pueden leer usando un teléfono móvil. Todos estos sensores pueden ser alimentados y leídos por cualquier dispositivo que disponga de conexión NFC.The implementation of near field communication (NFC) technology into smartphones grows rapidly due the use of this technology as a payment system. This, altogether with the fact that the energy generated by the phone can be used not only to communicate but for power transfer as well, the low-cost of the NFC chips, and the fact that the smartphones have connectivity to internet, makes possible and very interesting the design of battery-less sensing tags which information can be sent to the cloud, within the growing internet of things (IoT) scenario. This Thesis studies the feasibility of these sensors, analysing the maximum distance between reader and sensor to provide the necessary power, presents techniques to increase the range of operation, and analyses the effects of certain materials when they are near to the antennas. Several sensors have been designed and analysed and are presented in this work. These are: a tag that measures the soil moisture, the temperature and the relative humidity of the air to control the conditions of plants. A moisture sensor for diapers, printed on flexible material that adapts to the diaper shape. Two applications, one for pH estimation and another for assessing the degree of fruit ripening, based on a colour sensor. And finally, the feasibility of sensors in implants for medical applications is studied, analysing the effect of the body and proposing a system to increase the depth at which they can be read using a mobile phone. All of these sensors can be powered and read by any NFC enabled device

Hadoop-Based Intelligent Care System (HICS) : Analytical Approach for Big Data in IoT

The Internet of Things (IoT) is increasingly becoming a worldwide network of interconnected things that are uniquely addressable, via standard communication protocols. The use of IoT for continuous monitoring of public health is being rapidly adopted by various countries while generating a massive volume of heterogeneous, multisource, dynamic, and sparse high-velocity data. Handling such an enormous amount of high-speed medical data while integrating, collecting, processing, analyzing, and extracting knowledge constitutes a challenging task. On the other hand, most of the existing IoT devices do not cooperate with one another by using the same medium of communication. For this reason, it is a challenging task to develop healthcare applications for IoT that fulfill all user needs through real-Time monitoring of health parameters. Therefore, to address such issues, this article proposed a Hadoop-based intelligent care system (HICS) that demonstrates IoT-based collaborative contextual Big Data sharing among all of the devices in a healthcare system. In particular, the proposed system involves a network architecture with enhanced processing features for data collection generated by millions of connected devices. In the proposed system, various sensors, such as wearable devices, are attached to the human body and measure health parameters and transmit them to a primary mobile device (PMD). The collected data are then forwarded to intelligent building (IB) using the Internet where the data are thoroughly analyzed to identify abnormal and serious health conditions. Intelligent building consists of (1) a Big Data collection unit (used for data collection, filtration, and load balancing); (2) a Hadoop processing unit (HPU) (composed of Hadoop distributed file system (HDFS) and MapReduce); and (3) an analysis and decision unit. The HPU, analysis, and decision unit are equipped with a medical expert system, which reads the sensor data and performs actions in the case of an emergency situation. To demonstrate the feasibility and efficiency of the proposed system, we use publicly available medical sensory datasets and real-Time sensor traffic while identifying the serious health conditions of patients by using thresholds, statistical methods, and machine-learning techniques. The results show that the proposed system is very efficient and able to process high-speed WBAN sensory data in real time