12 research outputs found

    Autonomic Obstacle Detection and Avoidance in MANETs Driven by Cartography Enhanced OLSR

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    Validation platform implementation description - D5.2

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    This deliverable describes different test-beds for the validation of the architecture, algorithms and protocols for the operator governed opportunistic networking as defined in the OneFIT Project. Further on, this deliverable provides a description of the implementation of the OneFIT cognitive management systems CSCI and CMON as well as the C4MS protocol. Also, implementation of the blocks supporting the OneFIT system (JRRM, CCM, DSONPM, and DSM) is described. This document also describes the implementation of the OneFIT scenarios for opportunistic coverage extension, opportunistic capacity extension, infrastructure supported ad-hoc networking and device-to-device communication as well as opportunistic resource aggregation in the backhaul network

    Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

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    This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

    Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

    Get PDF
    This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of “volunteer mappers”. Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protection

    Results analysis and validation - D5.3

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    This deliverable describes the validation processes followed to assess the performance of the algorithms and protocols for the operator governed opportunistic networking as defined in the OneFIT Project. Therefore, this document includes the description of the set-up of the different validation platforms, the design of the test plans for each one of them, and the analysis of the results obtained from the tests. A per-scenario approach rather than a per-platform approach has been followed, so an additional analysis has been performed, gathering the results related to each scenario, in order to validate the premises stated to each one of them. The OneFIT concept has been therefore validated for all foreseen business scenarios

    Design and Evaluation of Compression, Classification and Localization Schemes for Various IoT Applications

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    Nowadays we are surrounded by a huge number of objects able to communicate, read information such as temperature, light or humidity, and infer new information through ex- changing data. These kinds of objects are not limited to high-tech devices, such as desktop PC, laptop, new generation mobile phone, i.e. smart phone, and others with high capabilities, but also include commonly used object, such as ID cards, driver license, clocks, etc. that can made smart by allowing them to communicate. Thus, the analog world of just a few years ago is becoming the a digital world of the Inter- net of Things (IoT), where the information from a single object can be retrieved from the Internet. The IoT paradigm opens several architectural challenges, including self-organization, self-managing, self-deployment of the smart objects, as well as the problem of how to minimize the usage of the limited resources of each device. The concept of IoT covers a lot of communication paradigms such as WiFi, Radio Frequency Identification (RFID), and Wireless Sensor Network (WSN). Each paradigm can be thought of as an IoT island where each device can communicate directly with other devices. The thesis is divided in sections in order to cover each problem mentioned above. The first step is to understand the possibility to infer new knowledge from the deployed device in a scenario. For this reason, the research is focused on the web semantic, web 3.0, to assign a semantic meaning to each thing inside the architecture. The sole semantic concept is unusable to infer new information from the data gathered; in fact, it is necessary to organize the data through a hierarchical form defined by an Ontology. Through the exploitation of the Ontology, it is possible to apply semantic engine reasoners to infer new knowledge about the network. The second step of the dissertation deals with the minimization of the usage of every node in a WSN. The main purpose of each node is to collect environmental data and to exchange hem with other nodes. To minimize battery consumption, it is necessary to limit the radio usage. Therefore, we implemented Razor, a new lightweight algorithm which is expected to improve data compression and classification by leveraging on the advantages offered by data mining methods for optimizing communications and by enhancing information transmission to simplify data classification. Data compression is performed studying the well-know Vector Quantization (VQ) theory in order to create the codebooks necessary for signal compression. At the same time, it is requested to give a semantic meaning to un- known signals. In this way, the codebook feature is able not only to compress the signals, but also to classify unknown signals. Razor is compared with both state-of-the-art compression and signal classification techniques for WSN . The third part of the thesis covers the concept of smart object applied to Robotic research. A critical issue is how a robot can localize and retrieve smart objects in a real scenario without any prior knowledge. In order to achieve the objectives, it is possible to exploit the smart object concept and localize them through RSSI measurements. After the localization phase, the robot can exploit its own camera to retrieve the objects. Several filtering algorithms are developed in order to mitigate the multi–path issue due to the wireless communication channel and to achieve a better distance estimation through the RSSI measurement. The last part of the dissertation deals with the design and the development of a Cognitive Network (CN) testbed using off the shelf devices. The device type is chosen considering the cost, usability, configurability, mobility and possibility to modify the Operating System (OS) source code. Thus, the best choice is to select some devices based on Linux kernel as Android OS. The feature to modify the Operating System is required to extract the TCP/IP protocol stack parameters for the CN paradigm. It is necessary to monitor the network status in real-time and to modify the critical parameters in order to improve some performance, such as bandwidth consumption, number of hops to exchange the data, and throughput
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