This master's thesis deals with creating an application for mobile devices with an Android operating system. The main task of this application is interpreting ALLL language commands. This allows any mobile device running this application to be a node of a wireless sensor network. First, well-known principles of wireless sensor networks, agents and ALLL language, which describes the agents in wireless sensor network, are explained in this project. The method for building the application on these bases follows. There are also some examples of agents interpreted by this application at the end.

The master thesis is concerned with problem of localization of nodes in wireless sensor network WSN implemented by ZigBee technology. The thesis provide description of ZigBee architecture involving signal description. The method of evaluating coordinates basically do not depend on used measuring methods. The method  of fingerprinting is included in separated category based on only statistical processing of RSSI data. Determination of coordinates of mobile node always needs finding out range, signal time of arrival (ToA) or angle of arrival (AoA) in respect to anchors node given dimension magnitude. The author found out three possible solutions for range measuring and one solution for angle of arrival measuring useable in context of ZigBee wireless sensor network. Finally the author discuss possibilities and constraints of ZigBee network with used measuring type.

>Magister Scientiae - MSc / The fifth-generation mobile network (5G) is a new global wireless standard that enables state-of-the-art mobile networks with enhanced cellular broadband services that support a diversity of devices. Even with the current worldwide advanced state of broadband connectivity, most rural and low-income settings lack minimum Internet connectivity because there are no economic incentives from telecommunication providers to deploy wireless communication systems in these areas. Using a team of Unmanned Aerial Vehicles (UAVs) to extend or solely supply the 5G coverage is a great opportunity for these zones to benefit from the advantages promised by this new communication technology. However, the deployment and applications of innovative technology in rural locations need extensive research.

Synchronization of distributed time difference of arrival (TDOA) sensor networks can be performed using reference signals from GPS satellites. This method provides high accuracy, but is vulnerable to jamming, and is not reliable enough to be used in military applications. A solution that does not depend on any signals transmitted from external actors is preferred. One way to achieve this is to use reference signals transmitted from a UAV. A UAV is suitable since only local synchronization for a geographically restricted area is necessary. The local synchronization is achieved by estimating the time-delay between the transmission and reception of a reference signal. The estimated time-delay can be used to detect drifts in the clocks of the TDOA sensors. This thesis analyzes com- mon reference signals, to evaluate which provide high accuracy for time-delay estimation, and what properties of the signals influence the estimation accuracy the most. The simulations show that the time-delay estimation performance can reach the same accuracy as synchronization against GPS for different types of signals. An increased bandwidth is more important than an increased signal length or signal-to-noise ratio to improve the estimation accuracy.

Although sensor planning in computer vision has been a subject of research for over two decades, a vast majority of the research seems to concentrate on two particular applications in a rather limited context of laboratory and industrial workbenches, namely 3D object reconstruction and robotic arm manipulation. Recently, increasing interest is engaged in research to come up with solutions that provide wide-area autonomous surveillance systems for object characterization and situation awareness, which involves portable, wireless, and/or Internet connected radar, digital video, and/or infrared sensors. The prominent research problems associated with multisensor integration for wide-area surveillance are modality selection, sensor planning, data fusion, and data exchange (communication) among multiple sensors. Thus, the requirements and constraints to be addressed include far-field view, wide coverage, high resolution, cooperative sensors, adaptive sensing modalities, dynamic objects, and uncontrolled environments. This article summarizes a new survey and analysis conducted in light of these challenging requirements and constraints. It involves techniques and strategies from work done in the areas of sensor fusion, sensor networks, smart sensing, Geographic Information Systems (GIS), photogrammetry, and other intelligent systems where finding optimal solutions to the placement and deployment of multimodal sensors covering a wide area is important. While techniques covered in this survey are applicable to many wide-area environments such as traffic monitoring, airport terminal surveillance, parking lot surveillance, etc., our examples will be drawn mainly from such applications as harbor security and long-range face recognition.

Many wireless sensor-based applications use LEACH as a preferred routing protocol owing to its unique features such as optimal sleeping time, minimum packet collisions, dynamic channel selection, and least power consumption. The traditional LEACH protocol wastes the transmission opportunities as it processes data only in an event occurring, leading to wastage of resources. To resolve this issue, this paper proposes a more robust Energy Enhanced Threshold Routing Protocol (ETH-LEACH) for WSNs. The working of ETH-LEACH is conceptualized in two parts. In the first part, TDMA is implemented to estimate the opportunistic paths to remove network overhead. Furthermore, in the second part, a threshold value is calculated for choosing the forwarder nodes. The proposed technique minimizes the energy usage of the sensor nodes and consequently enhances the network's lifetime by extending the duration of node death. The ETH-LEACH protocol is contrasted with the different variants of LEACH to verify its effectiveness. The experimental results show that the proposed ETH-LEACH protocol outperforms the traditional routing protocols. In this paper, the ETH-LEACH protocol performs nearly 54.6% efficient than LEACH, 47.6% efficient than Q-LEACH, 41.3% efficient than NR-LEACH, 33.6% efficient than LEACH-GA, and 29.7% efficient than LEACH-POS in reducing the usage of energy in the overall simulation.

A significant growth was witnessed in the field of Wireless Sensor Networks (WSNs), in the previous decade. The objective of this study has been Survey of micro controllers and short-range radio transceivers for wireless sensors and provide an extensive overview of micro controllers and RF-transceivers in the Market and compare the relevant properties for designing wireless sensor nodes. In the survey, RF-transvers from Nordic semiconductors is extensively presented for short-rang wireless protocols some of the protocols are RF-Communication Module, Bluetooth Low Energy Module, ZigBee module and Wi-Fi module.          In WSNs node design Power consumption is one the most important design issue, this thesis work present the different type of WSN protocols energy consumption efficiency and power consumption, compared and conclude graphically.        Microcontrollers are the main part of WSNs node for processing and gathering sensor data. There is different microcontroller’s products in the market however the WSN protocols presented in this thesis uses Cortex-M4 processor which is one of ARM product, the specification and comparison of this product with other products is presented.

Cette thèse s’intéresse au problème d’estimation et d’optimisation distribuée dans les réseaux asynchrones, c’est à dire en n’utilisant que des communication locales et asynchrones. A partir de multiples applications allant de l’apprentissage automatique aux réseaux de capteurs sans-fils, nous concevons et analysons théoriquement de nouveaux algorithmes résolvant trois problèmes de nature très différentes : la propagation de la plus grande des valeurs initiales, l’estimation de leur moyenne et enfin l’optimisation distribuée. / This thesis addresses the distributed estimation and optimization of a global value of interest over a network using only local and asynchronous (sometimes wireless) communications. Motivated by many different applications ranging from cloud computing to wireless sensor networks via machine learning, we design new algorithms and theoretically study three problems of very different nature : the propagation of the maximal initial value, the estimation of their average and finally distributed optimization.

The introduction of pavement, buildings, and other impervious surfaces to urban landscapes greatly influences the quantity and quality of urban stormwater runoff. In this study, we designed and implemented modern stormwater monitoring technologies to establish a “smart” stormwater sensor network within the Northwest Field Canal (NWFC), an urban water conveyance located in Logan, Utah, USA. This network was designed to collect flow and water quality data at high frequencies and simultaneously at multiple locations. The observatory’s innovative method of inter-site communication and changing sampling frequencies during storm events was able to capture short duration events at the upstream and downstream ends of the NWFC and at multiple outfalls in the canal simultaneously without human intervention. We then investigated statistical regression models between turbidity and TSS so as to predict TSS at high frequencies. Finally, the addition of the high-frequency discharge data in the calibration procedure for a stormwater simulation model developed using the Environmental Protection Agency’s Stormwater Management Model did little to improve model performance at the downstream end of the canal, but did provide important insight into the overall contribution of discharge from individual stormwater outfalls to the NWFC. The results of this study inform water professionals on how to build and operate automated monitoring systems and how to create high-frequency estimates of TSS and TP loads in urban water systems.

The main purpose of this dissertation is to define and solve problems on optimal sensing and actuating policies in Cyber-Physical Systems (CPSs). Cyber-physical system is a term that was introduced recently to define the increasing complexity of the interactions between computational hardwares and their physical environments. The problem of designing the ``cyber'' part may not be trivial but can be solved from scratch. However, the ``physical'' part, usually a natural physical process, is inherently given and has to be identified in order to propose an appropriate ``cyber'' part to be adopted. Therefore, one of the first steps in designing a CPS is to identify its ``physical'' part. The ``physical'' part can belong to a large array of system classes. Among the possible candidates, we focus our interest on Distributed Parameter Systems (DPSs) whose dynamics can be modeled by Partial Differential Equations (PDE). DPSs are by nature very challenging to observe as their states are distributed throughout the spatial domain of interest. Therefore, systematic approaches have to be developed to obtain the optimal locations of sensors to optimally estimate the parameters of a given DPS. In this dissertation, we first review the recent methods from the literature as the foundations of our contributions. Then, we define new research problems within the above optimal parameter estimation framework. Two different yet important problems considered are the optimal mobile sensor trajectory planning and the accuracy effects and allocation of heterogeneous sensors. Under the remote sensing setting, we are able to determine the optimal trajectories of remote sensors. The problem of optimal robust estimation is then introduced and solved using an interlaced ``online'' or ``real-time'' scheme. Actuation policies are introduced into the framework to improve the estimation by providing the best stimulation of the DPS for optimal parameter identification, where trajectories of both sensors and actuators are optimized simultaneously. We also introduce a new methodology to solving fractional-order optimal control problems, with which we demonstrate that we can solve optimal sensing policy problems when sensors move in complex media, displaying fractional dynamics. We consider and solve the problem of optimal scale reconciliation using satellite imagery, ground measurements, and Unmanned Aerial Vehicles (UAV)-based personal remote sensing. Finally, to provide the reader with all the necessary background, the appendices contain important concepts and theorems from the literature as well as the Matlab codes used to numerically solve some of the described problems.