Distributed and adaptive location identification system for mobile devices

Indoor location identification and navigation need to be as simple, seamless, and ubiquitous as its outdoor GPS-based counterpart is. It would be of great convenience to the mobile user to be able to continue navigating seamlessly as he or she moves from a GPS-clear outdoor environment into an indoor environment or a GPS-obstructed outdoor environment such as a tunnel or forest. Existing infrastructure-based indoor localization systems lack such capability, on top of potentially facing several critical technical challenges such as increased cost of installation, centralization, lack of reliability, poor localization accuracy, poor adaptation to the dynamics of the surrounding environment, latency, system-level and computational complexities, repetitive labor-intensive parameter tuning, and user privacy. To this end, this paper presents a novel mechanism with the potential to overcome most (if not all) of the abovementioned challenges. The proposed mechanism is simple, distributed, adaptive, collaborative, and cost-effective. Based on the proposed algorithm, a mobile blind device can potentially utilize, as GPS-like reference nodes, either in-range location-aware compatible mobile devices or preinstalled low-cost infrastructure-less location-aware beacon nodes. The proposed approach is model-based and calibration-free that uses the received signal strength to periodically and collaboratively measure and update the radio frequency characteristics of the operating environment to estimate the distances to the reference nodes. Trilateration is then used by the blind device to identify its own location, similar to that used in the GPS-based system. Simulation and empirical testing ascertained that the proposed approach can potentially be the core of future indoor and GPS-obstructed environments

Space-Time Hierarchical-Graph Based Cooperative Localization in Wireless Sensor Networks

It has been shown that cooperative localization is capable of improving both the positioning accuracy and coverage in scenarios where the global positioning system (GPS) has a poor performance. However, due to its potentially excessive computational complexity, at the time of writing the application of cooperative localization remains limited in practice. In this paper, we address the efficient cooperative positioning problem in wireless sensor networks. A space-time hierarchical-graph based scheme exhibiting fast convergence is proposed for localizing the agent nodes. In contrast to conventional methods, agent nodes are divided into different layers with the aid of the space-time hierarchical-model and their positions are estimated gradually. In particular, an information propagation rule is conceived upon considering the quality of positional information. According to the rule, the information always propagates from the upper layers to a certain lower layer and the message passing process is further optimized at each layer. Hence, the potential error propagation can be mitigated. Additionally, both position estimation and position broadcasting are carried out by the sensor nodes. Furthermore, a sensor activation mechanism is conceived, which is capable of significantly reducing both the energy consumption and the network traffic overhead incurred by the localization process. The analytical and numerical results provided demonstrate the superiority of our space-time hierarchical-graph based cooperative localization scheme over the benchmarking schemes considered.Comment: 14 pages, 15 figures, 4 tables, accepted to appear on IEEE Transactions on Signal Processing, Sept. 201

Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review

Animals play a profoundly important and intricate role in our lives today. Dogs have been human companions for thousands of years, but they now work closely with us to assist the disabled, and in combat and search and rescue situations. Farm animals are a critical part of the global food supply chain, and there is increasing consumer interest in organically fed and humanely raised livestock, and how it impacts our health and environmental footprint. Wild animals are threatened with extinction by human induced factors, and shrinking and compromised habitat. This review sets the goal to systematically survey the existing literature in smart computing and sensing technologies for domestic, farm and wild animal welfare. We use the notion of \emph{animal welfare} in broad terms, to review the technologies for assessing whether animals are healthy, free of pain and suffering, and also positively stimulated in their environment. Also the notion of \emph{smart computing and sensing} is used in broad terms, to refer to computing and sensing systems that are not isolated but interconnected with communication networks, and capable of remote data collection, processing, exchange and analysis. We review smart technologies for domestic animals, indoor and outdoor animal farming, as well as animals in the wild and zoos. The findings of this review are expected to motivate future research and contribute to data, information and communication management as well as policy for animal welfare

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

Indoor And Outdoor Real Time Information Collection in Disaster Scenario

A disaster usually severely harms human health and property. After a disaster, great amount of information of a disaster area is needed urgently. The information not only indicates the severity of the disaster, but also is crucial for an efficient search and rescue process. In order to quickly and accurately collect real time information in a disaster scenario, a mobile platform is developed for an outdoor scenario and a localization and navigation system for responders is introduced for an indoor scenario. The mobile platform has been integrated to the DIORAMA system. It is built with a 6-wheel robot chassis along with an Arduino microcontroller. Controlled by a mounted Android smartphone, the mobile platform can receive commands from incident commanders and quickly respond to the commands. While patrolling in a disaster area, a constant RFID signal is collected to improve the localization accuracy of victims. Pictures and videos are also captured in order to enhance the situational awareness of rescuers. The design of the indoor information collection is focused on the responder side. During a disaster scenario, it is hard to track responders’ locations in an indoor environment. In this thesis, an indoor localization and navigation system based on Bluetooth low energy and Android is developed for helping responders report current location and quickly find the right path in the environment. Different localization algorithms are investigated and implemented. A navigation system based on A­* is also proposed

Application of Swarm Intelligence in Disaster Management: A Review

The efficient use of Swarm Intelligence in Disaster management is discussed in this paper. Many lives are lost in Disaster affected area, the rescue team cannot reach everyone to rescue them this where Swarm Intelligence can be used. The Swarm Intelligence is a collective behavior to perform multiple task. SI can be used in searching and rescue operation in the disaster affected area, the swarm of Drones and bots deployed to locate the lives and give their exact location so that they can be rescued. The drones can analyze the area a give instruction to the ground bots. Obstacle avoidance can be used for clearing path for the rescue team to reach the location of the stuck person. Bots can combine together and work as one which increases their strength and may clear path. Swarm Intelligence is effective in many areas in Disaster Management

STAM: A System of Tracking and Mapping in Real Environments

We have implemented a system of tracking mobile robots and mapping an unstructured environment, using up to 25 wireless sensor nodes in an indoor setting. These sensor nodes form an ad hoc network of beacons, self-localize with respect to three anchor nodes, and then track the locations of mobile robots in the field. The system described here was motivated by search and rescue applications, and has been demonstrated in real physical environments

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

Combined Coverage Area Reporting and Geographical Routing in Wireless Sensor-Actuator Networks for Cooperating with Unmanned Aerial Vehicles

In wireless sensor network (WSN) applications with multiple gateways, it is key to route location dependent subscriptions efficiently at two levels in the system. At the gateway level, data sinks must not waste the energy of the WSN by injecting subscriptions that are not relevant for the nodes in their coverage area and at WSN level, energy-efficient delivery of subscriptions to target areas is required. In this paper, we propose a mechanism in which (1) the WSN provides an accurate and up-to-date coverage area description to gateways and (2) the wireless sensor network re-uses the collected coverage area information to enable efficient geographical routing of location dependent subscriptions and other messages. The latter has a focus on routing of messages injected from sink nodes to nodes in the region of interest. Our proposed mechanisms are evaluated in simulation

Langattomien anturiverkkojen sotilas-, agroteknologia- ja energiatutkimussovelluksia

The physical quantities nowadays are widely measured by using electronic sensors. Wireless sensor networks (WSNs) are low-cost, low-power electronic devices capable of collecting data using their onboard sensors. Some wireless sensor nodes are equipped with actuators, providing the possibility to change the state of the physical world. The ability to change the state of a physical system means that WSNs can be used in control and automation applications. This research focuses on appropriate system design for four different wireless measurement and control cases. The first case provides a hardware and software solution for camera integration to a wireless sensor node. The images are captured and processed inside the sensor node using low power computational techniques. In the second application, two different wireless sensor networks function in cooperation to overcome seeding problems in agricultural machinery. The third case focuses on indoor deployment of the wireless sensor nodes into an area of urban crisis, where the nodes supply localization information to friendly assets such as soldiers, firefighters and medical personnel. The last application focuses on a feasibility study for energy harvesting from asphalt surfaces in the form of heat.Fysikaaliset suureet mitataan nykyisin elektronisten anturien avulla. Langattomat anturiverkot ovat kustannustasoltaan edullisia, matalan tehonkulutuksen elektronisia laitteita, jotka kykenevät suorittamaan mittauksia niissä olevilla antureilla. Langattomat anturinoodit voidaan myös liittää toimilaitteisiin, jolloin ne voivat vaikuttaa fyysiseen ympäristöönsä. Koska langattomilla anturi- ja toimilaiteverkoilla voidaan vaikuttaa niiden fysikaalisen ympäristön tilaan, niiden avulla voidaan toteuttaa säätö- ja automaatiosovelluksia. Tässä väitöskirjaty össä suunnitellaan ja toteutetaan neljä erilaista langattomien anturi- ja toimilaiteverkkojen automaatiosovellusta. Ensimmäisenä tapauksena toteutetaan elektroniikka- ja ohjelmistosovellus, jolla integroidaan kamera langattomaan anturinoodiin. Kuvat tallennetaan ja prosessoidaan anturinoodissa vähän energiaa kuluttavia laskentamenetelmiä käyttäen. Toisessa sovelluksessa kahdesta erilaisesta langattomasta anturiverkosta koostuvalla järjestelmällä valvotaan siementen syöttöä kylvökoneessa. Kolmannessa sovelluksessa levitetään kaupunkiympäristössä kriisitilanteessa rakennuksen sisätiloihin langaton anturiverkko. Sen anturinoodit välittävät paikkatietoa rakennuksessa operoiville omille joukoille, jotka voivat tilanteesta riippuen olla esimerkiksi sotilaita, palomiehiä tai lääkintähenkilökuntaa. Neljännessä sovelluksessa toteutetaan langaton anturiverkko, jonka keräämää mittausdataa käytetään arvioitaessa lämpöenergian keräämismahdollisuuksia asfalttipinnoilta.fi=vertaisarvioitu|en=peerReviewed