Towards an intelligent and supportive environment for people with physical or cognitive restrictions

AmbienNet environment has been developed with the aim of demonstrating the feasibility of accessible intelligent environments designed to support people with disabilities and older persons living independently. Its main purpose is to examine in depth the advantages and disadvantages of pervasive supporting systems based on the paradigm of Ambient Intelligence for people with sensory, physical or cognitive limitations. Hence diverse supporting technologies and applications have been designed in order to test their accessibility, ease of use and validity. This paper presents the architecture of AmbienNet intelligent environment and an intelligent application to support indoors navigation for smart wheelchairs designed for validation purposes.Ministerio de Educación y Ciencia TIN2006-15617-C[01,02,03

Wireless distributed intelligence in personal applications

Tietokoneet ovat historian kuluessa kehittyneet keskustietokoneista hajautettujen, langattomasti toimivien järjestelmien suuntaan. Elektroniikalla toteutetut automaattiset toiminnot ympärillämme lisääntyvät kiihtyvällä vauhdilla. Tällaiset sovellukset lisääntyvät tulevaisuudessa, mutta siihen soveltuva tekniikka on vielä kehityksen alla ja vaadittavia ominaisuuksia ei aina löydy. Nykyiset lyhyen kantaman langattoman tekniikan standardit ovat tarkoitettu lähinnä teollisuuden ja multimedian käyttöön, siksi ne ovat vain osittain soveltuvia uudenlaisiin ympäristöälykkäisiin käyttötarkoituksiin. Ympäristöälykkäät sovellukset palvelevat enimmäkseen jokapäiväistä elämäämme, kuten turvallisuutta, kulunvalvontaa ja elämyspalveluita. Ympäristöälykkäitä ratkaisuja tarvitaan myös hajautetussa automaatiossa ja kohteiden automaattisessa seurannassa. Tutkimuksen aikana Seinäjoen ammattikorkeakoulussa on tutkittu lyhyen kantaman langatonta tekniikkaa: suunniteltu ja kehitetty pienivirtaisia radionappeja, niitten ohjelmointiympäristöä sekä langattoman verkon synkronointia, tiedonkeruuta ja reititystä. Lisäksi on simuloitu eri reititystapoja, sisäpaikannusta ja kaivinkoneen kalibrointia soveltaen mm. neurolaskentaa. Tekniikkaa on testattu myös käytännön sovelluksissa. Ympäristöälykkäät sovellusalueet ovat ehkä nopeimmin kasvava lähitulevaisuuden ala tietotekniikassa. Tutkitulla tekniikalla on runsaasti uusia haasteita ihmisten hyvinvointia, terveyttä ja turvallisuutta lisäävissä sovelluksissa, kuten myös teollisuuden uusissa sovelluksissa, esimerkiksi älykkäässä energiansiirtoverkossa.The development of computing is moving from mainframe computers to distributed intelligence with wireless features. The automated functions around us, in the form of small electronic devices, are increasing and the pace is continuously accelerating. The number of these applications will increase in the future, but suitable features needed are lacking and suitable technology development is still ongoing. The existing wireless short-range standards are mostly suitable for use in industry and in multimedia applications, but they are only partly suitable for the new network feature demands of the ambient intelligence applications. The ambient intelligent applications will serve us in our daily lives: security, access control and exercise services. Ambient intelligence is also adopted by industry in distributed amorphous automation, in access monitoring and the control of machines and devices. During this research, at Seinäjoki University of Applied Sciences, we have researched, designed and developed short-range wireless technology: low-power radio buttons with a programming environment for them as well as synchronization, data collecting and routing features for the wireless network. We have simulated different routing methods, indoor positioning and excavator calibration using for example neurocomputing. In addition, we have tested the technology in practical applications. The ambient intelligent applications are perhaps the area growing the most in information technology in the future. There will be many new challenges to face to increase welfare, health, security, as well as industrial applications (for example, at factories and in smart grids) in the future.fi=vertaisarvioitu|en=peerReviewed

System Architecture for Low-Power Ubiquitously Connected Remote Health Monitoring Applications With Smart Transmission Mechanism

We present a novel smart transmission technique with seamless handoff mechanism to achieve ubiquitous connectivity using multiple on-chip radios targeting remote health monitoring applications. For the first time to the best of our knowledge, a system architecture for low-power ubiquitously connected multiparametric remote health monitoring system is proposed in this paper. The architecture proposed uses a generic adaptive rule engine for classifying the collected multiparametric data from patient and smartly transmit the data when only needed. The on-chip seamless handoff mechanism proposed aids for the ubiquitous connectivity with a very good energy savings by intelligent controlling of the multiple on-chip radios. The performance analysis of the proposed on-chip seamless handoff mechanism along with adaptive rule engine-based smart transmission mechanism achieves on an average of 50.39% of energy saving and 51.01% reduction in duty cycle of transmitter taken over 20 users compared with the continuous transmission. From the hardware complexity analysis made on the proposed seamless handoff controller and adaptive rule engine concludes that they require only 2082 CMOS transistors for real-time implementation

Indoor Localization Based on Wireless Sensor Networks

Indoor localization techniques based on wireless sensor networks (WSNs) have been increasingly used in various applications such as factory automation, intelligent building, facility management, security, and health care. However, existing localization techniques cannot meet the accuracy requirement of many applications. Meanwhile, some localization algorithms are affected by environmental conditions and cannot be directly used in an indoor environment. Cost is another limitation of the existing localization algorithms. This thesis is to address those issues of indoor localization through a new Sensing Displacement (SD) approach. It consists of four major parts: platform design, SD algorithm development, SD algorithm improvement, and evaluation. Platform design includes hardware design and software design. Hardware design is the foundation for the system, which consists of the motion sensors embedded on mobile nodes and WSN design. Motion sensors are used to collect motion information for the localizing objects. A WSN is designed according to the characteristics of an indoor scenario. A Cloud Computing based system architecture is developed to support the software design of the proposed system. In order to address the special issues in an indoor environment, a new Sensing Displacement algorithm is developed, which estimates displacement of a node based on the motion information from the sensors embedded on the node. The sensor assembly consists of acceleration sensors and gyroscope sensors, separately sensing the acceleration and angular velocity of the localizing object. The first SD algorithm is designed in a way to be used in a 2-D localization demo to validate the proposal. A detailed analysis of the results of 2-D SD algorithm reveals that there are two critical issues (sensor’s noise and cumulative error) affecting the measurement results. Therefore a low-pass filter and a modified Kalman filter are introduced to solve the issue of sensor’s noises. An inertia tensor factor is introduced to address the cumulative error in a 3-D SD algorithm. Finally, the proposed SD algorithm is evaluated against the commercial AeroScout (WiFi-RFID) system and the ZigBee based Fingerprint algorithm

CIR Parametric Rules Precocity For Ranging Error Mitigation In IR-UWB

The cutting-edge technology to support high ranging accuracy within the indoor environment is Impulse Radio Ultra Wide Band (IR-UWB) standard. Besides accuracy, IR-UWB’s low-complex architecture and low power consumption align well with mobile devices. A prime challenge in indoor IR-UWB based localization is to achieve a position accuracy under non-line-of-sight (NLOS) and multipath propagation (MPP) conditions. Another challenge is to achieve acceptable accuracy in the conditions mentioned above without any significant increase in latency and computational burden. This dissertation proposes a solution for addressing the accuracy and reliability problem of indoor localization system satisfying acceptable delay or computational complexity overhead. The proposed methodology is based on rules for identification of line-of-sight (LOS) and NLOS and the range error bias estimation and correction due to NLOS and MPP conditions. The proposed methodology provides accuracy for two major application domains, namely, wireless sensor networks (WSNs) and indoor tracking and navigation (ITN). This dissertation offers two different solutions for the localization problem. The first solution is a rules-based classification of LOS / NLOS and geometric-based range correction for WSN. In the first solution, the Boolean logic based classification is designed for identification of LOS/NLOS. The logic is based on channel impulse response (CIR) parameters. The second solution is based on fuzzy logic. The fuzzy based solution is appealing well for the stringent precision requirements in ITN. In this solution, the parametric Boolean logic from the first solution is converted and expanded into rules. These rules are implemented into a fuzzy logic based mechanism for designing a fuzzy inference system. The system estimates the ranging errors and correcting unmitigated ranges. The expanded rules and designed methodology are based on theoretical analysis and empirical observations of the parameters. The rules accommodate the parameters uncertainties for estimating the ranging error through the relationship between the input parameters uncertainties and ranging error using fuzzy inference mechanism. The proposed solutions are evaluated using real-world measurements in different indoor environments. The performance of the proposed solutions is also evaluated in terms of true classification rate, residual ranging errors’ cumulative distributions and probability density distributions, as well as outage probabilities. Evaluation results show that the true classification rate is more than 95%. Moreover, using the proposed fuzzy logic based solution, the residual errors convergence of 90% is attained for error threshold of 10 cm, and the reliability of the localization system is also more than 90% for error threshold of 15 cm

Evaluation of an indoor localization system for a mobile robot

Although indoor localization has been a wide researched topic, obtained results may not fit the requirements that some domains need. Most approaches are not able to precisely localize a fast moving object even with a complex installation, which makes their implementation in the automated driving domain complicated. In this publication, common technologies were analyzed and a commercial product, called Marvelmind Indoor GPS, was chosen for our use case in which both ultrasound and radio frequency communications are used. The evaluation is given in a first moment on small indoor scenarios with static and moving objects. Further tests were done on wider areas, where the system is integrated within our Robotics Operating System (ROS)-based self-developed 'Smart PhysIcal Demonstration and evaluation Robot (SPIDER)' and the results of these outdoor tests are compared with the obtained localization by the installed GPS on the robot. Finally, the next steps to improve the results in further developments are discussed

Wi-Fi Finger-Printing Based Indoor Localization Using Nano-Scale Unmanned Aerial Vehicles

Explosive growth in the number of mobile devices like smartphones, tablets, and smartwatches has escalated the demand for localization-based services, spurring development of numerous indoor localization techniques. Especially, widespread deployment of wireless LANs prompted ever increasing interests in WiFi-based indoor localization mechanisms. However, a critical shortcoming of such localization schemes is the intensive time and labor requirements for collecting and building the WiFi fingerprinting database, especially when the system needs to cover a large space. In this thesis, we propose to automate the WiFi fingerprint survey process using a group of nano-scale unmanned aerial vehicles (NAVs). The proposed system significantly reduces the efforts for collecting WiFi fingerprints. Furthermore, since these NAVs explore a 3D space, the WiFi fingerprints of a 3D space can be obtained increasing the localization accuracy. The proposed system is implemented on a commercially available miniature open-source quadcopter platform by integrating a contemporary WiFi - fingerprint - based localization system. Experimental results demonstrate that the localization error is about 2m, which exhibits only about 20cm of accuracy degradation compared with the manual WiFi fingerprint survey methods

Applications of Soft Computing in Mobile and Wireless Communications

Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications