Objektu monitorings ar zema enerģijas patēriņa iegultām iekārtām un heterogēniem bezvadu sensoru tīkliem

Elektroniskā versija nesatur pielikumusBezvadu sensoru tīkli ir kļuvuši par neatņemamu daļu no visuresošās skaitļošanas (Ubiquitous Computing) un lietu interneta (Internet of Things). Darba ietvaros izstrādāta un aprakstīta vispārīgā metode iegulto sensoro iekārtu izveidei, kuru pielietojot, iespējams radīt rīkus objektu monitoringam un datu ievākšanai, kas, savukārt, izmanto zema enerģijas patēriņa iegultas sensorās iekārtas un heterogēnus bezvadu sensoru tīklus. Darba gaitā izstrādātā metode pielietota, lai radītu rīku kopumu, kas piemēroti savvaļas dzīvnieku, piemēram, Eirāzijas lūšu (Lynx lynx) vai Eirāzijas pelēko vilku (Canis lupus lupus) monitoringam un aktivitāšu noteikšanai. Darbā izvirzītā hipotēze arī aprobēta un iegūtie rezultāti apkopoti, pielietojot radītos rīkus auto orientēšanās pasākumu dalībnieku izsekošanai. Daļa no darba rezultātiem tiek pielietoti datu ieguvei un apmaiņai, veicot apvidus izpēti pirms saules un vēja enerģijas ieguves iekārtu uzstādīšanas. Darbā sasniegtie rezultāti, radot dažāda pielietojuma iegultās sensorās iekārtas balstoties uz piedāvāto vispārīgo metodi, pierāda, ka tā ir pielietojama. Atslēgas vārdi Bezvadu sensoru tīkli, objektu monitorings, savvaļas dzīvnieki, komunikācija tīklā, pret aizturēm noturīga datu pārraide.Wireless sensor networks have become an integral part of the ubiquitous computing and the Internet of Things. During research has been developed and descrobed general method for creating embedded sensor equipment. By applying in one can create tools for object monitoring and data collection using low-power embedded sensor equipment and heterogeneous wireless sensor networks. In the course of work the method was applied to create the tool package suitable for monitoring and determination of activities of wild animals, i.e. Eurasian lynxes (Lynx lynx) or Eurasian grey wolves (Canis lupus lupus). Some of works hypotheses are evaluated and results are categorized by applying them to track participants of car orienteering events. As well some assumptions of research are evaluated based on data collection and exchange in monitoring of sites of future renewable energy plants. The results achieved by creating various usage embedded sensor devices shows that genral method described in thesis is applicable. Keywords: Wireless Sensor Networks, Object Monitoring, Wilds Animals, Network Communication, Delay and Disruption Tolerant Networking

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

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