Fingerprint indoor positioning based on user orientations and minimum computation time

Indoor Positioning System (IPS) has an important role in the field of Internet of Thing. IPS works based on many existing radio frequency technologies. One of the most popular methods is WLAN Fingerprint because this technology has been installed widely inside buildings and it provides a high level of accuracy. The performance is affected by people who hold mobile devices (user) and also people around the users. This research aimed to minimize the computation time of kNN searching process. The results showed that when the value of k in kNN was greater, the computation time increased, especially when using Cityblock and Minkowski distance function. The smallest average computation time was 2.14 ms, when using Cityblock. Then the computational time for Euclidean and Chebychev were relatively stable, i.e. 2.2 ms and 2.23 ms, respectively

Modelling the Effect of Human Body around User on Signal Strength and Accuracy of Indoor Positioning

WLAN indoor positioning system (IPS) has high accurate of position estimation and minimal cost. However, environmental conditions such as the people presence effect (PPE) greatly influence WLAN signal and it will decrease the accuracy. This research modelled the effect of people around user on signal strength and the accuracy. We have modelled the human body around user effects by proposed a general equation of decrease in RSSI as function of position, distance, and number of people. RSSI decreased from 5 dBm to 1 dBm when people in LOS position, and start from 0.5 dBm to 0.3 dBm when people in NLOS position. The system accuracy decreases due to the presence of people. When the system in NLOS case (ΔRSSI = 0.5 dBm), the presence of people causes a decrease in accuracy from 33% to 57%. Then the accuracy decrease from 273% to 334% in LOS case (ΔRSSI = 5 dBm)

Sistema de monitoreo para pacientes en zona de cirugía utilizando geolocalización

Trabajo de InvestigaciónEste documento se estructura de la siguiente manera; primero se presenta la justificación y los antecedentes donde se busca y analiza las problemáticas que tienen los centros médicos específicamente en las zonas de cirugía. Seguidamente, en el marco de referencia se definen y explican los conceptos básicos para entender este trabajo, así como los requerimientos en los que se tiene en cuenta los módulos (captación, procesamiento, transmisión, almacenamiento y visualización), para seguir así con el diseño e implementación del prototipo.INTRODUCCIÓN 1. GENERALIDADES 2. DESCRIPCIÓN DE LOS COMPONENTES 3. IMPLEMENTACIÓN 4. PRUEBAS DEL FUNCIONAMIENTO 5. VALIDACIÓN DEL DISPOSITIVO 6. DESCRIPCIÓN ECONOMICA DEL PROYECTO 7. CONCLUSIONES 8. BIBLIOGRAFÍA ANEXOSPregradoIngeniero Electrónic

Economic sustainability in franchising: a model to predict franchisor success or failure

As a business model, franchising makes a major contribution to gross domestic product (GDP). A model that predicts franchisor success or failure is therefore necessary to ensure economic sustainability. In this study, such a model was developed by applying Lasso regression to a sample of franchises operating between 2002 and 2013. For franchises with the highest likelihood of survival, the franchise fees and the ratio of company-owned to franchised outlets were suited to the age of the franchise. Surviving franchises were those that opened franchised outlets at a sustainable pace, increased the franchise fee as intangible assets increased, and effectively managed profitability and efficiency

Discovering location based services: A unified approach for heterogeneous indoor localization systems

The technological solutions and communication capabilities offered by the Internet of Things paradigm, in terms of raising availability of wearable devices, the ubiquitous internet connection, and the presence on the market of service-oriented solutions, have allowed a wide proposal of Location Based Services (LBS). In a close future, we foresee that companies and service providers will have developed reliable solutions to address indoor positioning, as basis for useful location based services. These solutions will be different from each other and they will adopt different hardware and processing techniques. This paper describes the proposal of a unified approach for Indoor Localization Systems that enables the cooperation between heterogeneous solutions and their functional modules. To this end, we designed an integrated architecture that, abstracting its main components, allows a seamless interaction among them. Finally, we present a working prototype of such architecture, which is based on the popular Telegram application for Android, as an integration demonstrator. The integration of the three main phases –namely the discovery phase, the User Agent self-configuration, and the indoor map retrieval/rendering– demonstrates the feasibility of the proposed integrated architectur

Modelling the effect of human body around user on signal strength and accuracy of indoor positioning

WLAN indoor positioning system (IPS) has high accurate of position estimation and minimal cost. However, environmental conditions such as the people presence effect (PPE) greatly influence WLAN signal and it will decrease the accuracy. This research modelled the effect of people around user on signal strength and the accuracy. We have modelled the human body around user effects by proposed a general equation of decrease in signal strength as function of position, distance, and number of people. Signal strength decreased from 5 dBm to 1 dBm when people in line of sight (LOS) position, and start from 0.5 dBm to 0.3 dBm when people in non-line of sight (NLOS) position. The system accuracy decreases due to the presence of people. When the system is in NLOS case, the presence of people causes a decrease in accuracy from 33% to 57%. Then the accuracy decrease from 273% to 334% in LOS case

Design criteria for Indoor Positioning Systems in hospitals using technological, organizational and individual perspectives

This dissertation considers three different studies that handle Indoor Positioning Systems (IPS) in hospitals. Study 1 uses the Reasoned Action Approach by questioning hospital visitors and employees about their intention to use IPS in hospitals. Study 2 reviews IPS in hospitals. Study 3 is based on the results of the first two studies. It handles expert interviews that were conducted with different hospitals and IPS developers to evaluate the determined propositions. Then, the insights were used to conduct and evaluate experiments by testing an ultrasound-based IPS for hospitals

Wi-Fi Fingerprinting Based Room Level Indoor Localization Framework Using Ensemble Classifiers

Over the past decennium, Wi-Fi fingerprinting based indoor localization has seized substantial attention. Room level indoor localization can enable numerous applications to increase their diversity by incorporating user location. Real-world commercial scale deployments have not been realized because of difficulty in capturing radio propagation models. In case of fingerprinting based approaches, radio propagation model is implicitly integrated in the gathered fingerprints providing more realistic information as compared to empirical propagation models. We propose ensemble classifiers based indoor localization using Wi-Fi fingerprints for room level prediction. The major advantages of the proposed framework are, ease of training, ease to set up framework providing high room-level accuracy with trifling response time making it viable and appropriate for real time applications. It performs well in comparison with recurrently used ANN (Artificial Neural Network) and kNN (k-Nearest Neighbours) based solutions. Experiments performed showed that on our real-world Wi-Fi fingerprint dataset, our proposed approach achieved 89% accuracy whereas neural network and kNN based best found configurations achieved 85 and 82% accuracy respectively