Generic sensor network architecture for wireless automation (GENSEN)

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Wind energy harvester interface for sensor nodes

The research topic is developping a power converting interface for the novel FLEHAP wind energy harvester allowing the produced energy to be used for powering small wireless nodes. The harvester\u2019s electrical characteristics were studied and a strategy was developped to control and mainting a maximum power transfer. The electronic power converter interface was designed, containing an AC/DC Buck-Boost converter and controlled with a low power microcontroller. Different prototypes were developped that evolved by reducing the sources of power loss and rendering the system more efficient. The validation of the system was done through simulations in the COSMIC/DITEN lab using generated signals, and then follow-up experiments were conducted with a controllable wind tunnel in the DIFI department University of Genoa. The experiment results proved the functionality of the control algorithm as well as the efficiency that was ramped up by the hardware solutions that were implemented, and generally met the requirement to provide a power source for low-power sensor nodes

Accurate monitoring and fault detection in wind measuring devices through wireless sensor networks

Many wind energy projects report poor performance as low as 60% of the predicted performance. The reason for this is poor resource assessment and the use of new untested technologies and systems in remote locations. Predictions about the potential of an area for wind energy projects (through simulated models) may vary from the actual potential of the area. Hence, introducing accurate site assessment techniques will lead to accurate predictions of energy production from a particular area. We solve this problem by installing a Wireless Sensor Network (WSN) to periodically analyze the data from anemometers installed in that area. After comparative analysis of the acquired data, the anemometers transmit their readings through a WSN to the sink node for analysis. The sink node uses an iterative algorithm which sequentially detects any faulty anemometer and passes the details of the fault to the central system or main station. We apply the proposed technique in simulation as well as in practical implementation and study its accuracy by comparing the simulation results with experimental results to analyze the variation in the results obtained from both simulation model and implemented model. Simulation results show that the algorithm indicates faulty anemometers with high accuracy and low false alarm rate when as many as 25% of the anemometers become faulty. Experimental analysis shows that anemometers incorporating this solution are better assessed and performance level of implemented projects is increased above 86% of the simulated models

Low-energy sensor network protocols and application to smart wind turbines

The Internet of Things (IoT) has shown promise as an enabling technology for a wide variety of applications, from smart homes to infrastructure monitoring and management. However, a number of challenges remain before the grand vision of an everything-sensed, everything-connected world can be achieved. One of these challenges is the energy problem: how can embedded, networked sensor devices be sustainably powered over the lifetime of an application? To that end, this dissertation focuses on reducing energy consumption of communication protocols in wireless sensor networks and the IoT. The motivating application is wind energy infrastructure monitoring and management, or smart wind turbines. A variety of approaches to low-energy protocol design are studied. The result is a family of low-energy communication protocols, including one specifically designed for nodes deployed on wind turbine blades. This dissertation also presents background information on monitoring and management of wind turbines, and a vision of how the proposed protocols could be integrated and deployed to enable smart wind turbine applications

Design and development of an SDN robotic system with intelligent openflow IOT testbeds for power assessment, prediction and fault management

This thesis was submitted for the award of Docctor of Philosophy and was awarded by Brunel University LondonCurrent wind turbine and power grid industry have relatively little research and development with regards to implementing novel communication network and intel- ligent system to overcome issues that pertain to network failure and lack of monitor- ing. Wind turbine location could be a big concern when it comes to identifying an efficient location for future wind turbine and the impact of a site with non-efficient meteorological parameters can result in relocation of a wind turbine and revenue- loss. Unplanned wind turbine shutdowns that are considered to be one of the major revenue-loss factors of a modern wind farm business. Typically, the unplanned wind turbine shutdown is a result of sensors fail due to harsh environment challenges that prevent hardware status from being available on the monitoring system. The above mentioned research problems pertain to wind turbine site assessment and predic- tion of power. In this thesis, a novel programmable software-defined robotics and IoT testbeds are proposed with the fusion of Artificial Intelligence and optimiza- tion methods to solve specific problems related to wind turbine site assessment and fault management. The site selection process is implemented using proposed aerial and ground robotic systems that are incorporated with Software-Defined Networks and OpenFlow switching capabilities. A second stage development of the system is proposing a prediction platform that run on the aerial robot cluster using neural net- works optimization regression techniques. To overcome the unplanned wind turbine network outage, an IoT micro cloud cluster system is proposed that act as immedi- ate fail-over platform to provide continuous health readings of the wind turbine to ensure the turbine in question will not get shutdown unnecessarily. The proposed system help in minimizing revenue-loss caused by stopping a wind turbine from op- eration and help maintain generated power stability on the grid. Additionally, since large wind farms require an agile and scalable management of selecting the most efficient wind turbine location install. Thus, a softwarized cognitive routing proto- col is proposed. The group of quadcopters is a redundant failover Software-Defined Network/OpenFlow system that can cover every single way point of the farm land. Although, power consumption is essential for the continuity the service, a Software- Defined charging system testbed is proposed that uses inductive power transfer wit

ANT colony optimization based optimal path selection and data gathering in WSN

A data aggregation is an essential process in the field of wireless sensor network to deal with base station and sink node. In current data gathering mechanism, the nearest nodes to the sink receives data from all the other nodes and shares it to the sink. The data aggregation process is utilized to increase the capability and efficiency of the existing system. In existing technique, the possibility of data loss is high this may leads to energy loss therefore; the efficiency and performance are damaged. In order to overcome these issues, an effective cluster based data gathering technique is developed. Here the optimal cluster heads are selected which is used for transmission with low energy consumption. The optimal path for mobile sink (MS) is done by Ant Colony Optimization (ACO) algorithm. It provides efficient path along with MS to collect the data along with Cluster centroid. The performance of the proposed method is analyzed in terms of delay, throughput, lifetime, etc.</p

WeatherLAN - A Local Area Network for Monitoring and Control

Monitoring of nature behaviours is a crucial part in many applications. The need for monitoring is in fact unavoidable in systems where independent operation of a system is needed. On locations where no cabled infrastructure is available it is necessary to use wireless link to interconnect the location with the Internet. GPRS is a cheap solution for transferring data over such areas where cables are not available by using operator public cellular network. In this thesis a wireless sensor network is integrated with a GPRS module to support multiple measurement points and GPRS link as backbone connection to remote location. Security issues related to embedded systems and the use of public networks is investigated and one possible solution presented. Vaisala WXT520 weather transmitter is added to the system to measure the weather at the network location which would be needed to remotely support the distributed energy production by wind turbine generator, solar panels and backup diesel generator. The system prevent to be one solution that would enable remote control of the local energy production.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Energy Harvesting Solution for the UWASA Node: Applications for Wind Turbine Monitoring

The aim of this thesis was to develop an energy harvesting solution for the UWASA Node for wind power station applications. Energy harvesting is the process by which small amounts of ambient energy is collected for use by electronics such as wireless sensor nodes. The developed energy harvesting solution is capable of supplying enough energy for the UWASA Node to perform a wide variety of tasks indefinitely, without the need for changing its battery. The wireless sensor node can for example read sensors at high sampling rates and store or wirelessly transmit these readings. It can also perform complex computations and react to changes in its environment. One intended use was monitoring vibrations of wind turbines blades, but field tests have yet to be done. This master’s thesis builds on the findings of my bachelor’s thesis, Höglund (2014) in the references. In the bachelor’s thesis different methods of energy harvesting were in-vestigated to find the most suitable methods for this project. In this master’s thesis a prototype energy harvester and energy management circuit was developed and tested. The prototype is capable of harvesting tens of milliwatts from a small solar cell. It could also be modified to harvest another ambient energy source or several sources at once. Every part of the energy harvester and energy management circuit is discussed in detail and laboratory tests are presented. Different means of maximum power point tracking were tested and evaluated. The prototype energy harvester was built using a modular approach so that energy harvesting from multiple sources of energy easily can be ac-complished by adding a few components for each source to the harvesting circuit. The programming of the sensor node also needs to be adapted so that it runs optimally from the harvested energy by scheduling measurements and wireless communication. A low-power real-time clock and a latching switch were included on the prototype PCB for switching on and off the power to the sensor node completely in order to consume as little energy as possible when the sensor node is inactive.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

A simulation into the physical and network layers of optical communication network for the subsea video surveillance of illicit activity.

Criminal activity is increasingly entering the ocean subsurface with acts such as illegal fishing and narco-submarining becoming points of contention. This among other illicit acts taking place in this domain imply a need for surveillance to render these activities apparent. However, subsurface Underwater Sensor Networking which is central to the surveillance is still generations behind terrestrial networking, therefore it is still challenging to monitor for subsurface activities. This is since the current signal transmission standard, acoustic communication, is limited in practical bandwidth and thus channel data-rate, this is, however, caveated with omni-directional propagation and supreme range rendering it reliable but incapable of carrying video or other data intensive sensor information. There is, however, an emerging technology based on optical (visible light) communication that can accommodate surveillance applications with superior data rates and energy savings. This investigation demonstrates how theoretically it is possible to achieve a network of underwater channels capable of sustaining a multimedia feed for monitoring subsurface activity using modern optical communication when in compared to an acoustic network. In addition, a simple topology was investigated that shows how the range limitations of this signaling can be extended by adding floating relay nodes. Through simulations in Network Simulator 3 (NS-3)/Aquasim-NG software it is shown that Visible Light wireless communication in visible light networks have a channel capacity high enough to carry out monitoring in strategic areas, referencing, optical modems that are available in the market. This implies that data-rates of 10 Mb/s are possible for the real-time video surveillance