Smart distribution grids will be a combination of existing electrical networks controlled by distributed software applications communicating via communication networks. This means that not only the reliability of individual technologies are crucial, but the interoperability is also pivotal for the robustness of the smart distribution network. These individual research areas electrical network, distributed software controller and communication network have their corresponding fault handling strategies and several proven solutions exist to ensure reliability.
The objective of our work is to integrate the solutions from these individual technologies. We focus on the interoperability and integration of individual fault handling strategies that are essential for improving the reliability and robustness of the overall smart distribution network. In this paper, we describe our approach in creating a single solution from the existing individual strategies to create a robust smart distribution network. We also present the details of the demonstrator design that is being built to evaluate our approach.
Government agencies, public institutions, and private companies in India have worked over six decades to empower Bottom of the Pyramid BoP or rural communities through various policies and interventions. Eighty-five percent of these technological interventions failed to create an impact as they lacked a holistic approach, scalability, sustainability, and effective interagency coordination. The model aims to create a virtual ecosystem that will enable field practitioners, researchers, policymakers, and other stakeholders to plan, design, implement, and review scalable and sustainable interventions.
In most of the real world wireless sensor network deployments, the energy utilization is a critical factor as the nodes are battery powered. In most of the real-world deployments it is observed that the sensing subsystem consumes higher power. In order to extend the lifetime of such systems it is required to reduce the sensing energy than communication energy. We have deployed a system for monitoring Landslides in India consists of geo-physical sensors and used solar panels to power these sensor nodes. The decision making in favor of Landslide occurrence is based on the maximum values obtained from the high priority sensors.
As this maximum value is not frequently changing in the deployment, locating the sensor node with maximum value allows us to switch off the other sensors for a predetermined period of time. This work proposes an optimal balanced network topology for delay minimization by parallelizing data aggregation operation in each sub-network. The sensor node switch off schemes on the top of delay minimized topology enables the optimal utilization of the available solar power.
The analysis of these mechanisms shows that, more number of nodes can be powered with the available source of energy and can increase the network life time. Marine fishermen risk their lives when they go as far as km from the shore on a fishing trip lasting days. They are completely cut off from the mainland. Cellular coverage exists only up to km from the shore. In emergency situations, the fishermen have no way to call for help. Even under normal conditions, prolonged isolation from their family and friends causes mental depression.
Since the marine fishermen are not economically well off especially in the developing countries, there has not been much commercial interest in addressing this problem. It is not seen as a profitable business proposition. However, addressing this problem will benefit the marine fishermen community immensely.
Our center conducted interviews with several fishermen to understand this problem and came up with a cost-effective solution. The solution enables the fishermen to use the smart phones which they own already to get internet at sea using Wi-Fi. The onshore base station is installed on a tower at a height of m. Boats are also used as mobile base stations to extend the range of the network. A pilot deployment is in progress in a coastal village community in Kerala, India, to gain operational experience. Water scarcity has been a major thrusting issue in rural India, warrantinga high demand to design and implement different water distribution networks for easy and efficient use of existing water sources.
Both macro and micro level systems exist of which, macro level water distribution networks have higher capital and maintenance costs. This is due to its size and the remote beneficiaries to which it caters. This paper describes the design of one such water distribution system in two rural villages in India whose design considerations includes the local community needs, availability of labor, local resources, climate, cost, and time for implementation. This paper also compares the micro and macro water distribution network's impact on sustainability.
Sustainability is defined in terms of water wastage, usage rate, source capacity, total network length, cost of deployment, source recharge, and the network leakage rate. The paper also draws insights on the socio-economic impact of the project carried out in these two states. Fishermen at sea lack proper localization and tracking systems leading to increased loss of life at sea due to disasters, engine failure, and collision with ships.
A taxonomy of cross layer routing metrics for wireless mesh networks
To reduce the impact of such scenarios we need an efficient localization and tracking algorithm for approximate localization of fishing vessels in a spatio — temporal domain. In this work, we have analyzed few existing algorithms for localization of mobile sensor nodes and based on these results, an Enhanced Chord Based Localization Algorithm ECLA has been designed and developed.
The proposed algorithm is implemented and extensively tested on the basis of different performance parameters such as mobility, localization accuracy, execution time etc. The experimental results clearly show that the proposed algorithm has better localization accuracy compared to the existing localization algorithms.
The accuracy of the proposed ECLA algorithm is In a maritime environment, affordable long range communication network for fishing vessels are highly necessary for safety at sea and to communicate to shore and back to the fishing vessels. The existing communication architecture faces major challenges in achieving seamless connectivity due to the mobility of fishing vessels, lack of backbone infrastructure, propagation effects, and fault tolerance. In this work, we explored the capability of Delay Tolerant Networks DTN for providing better connectivity under the above mentioned parameters.
These protocols were simulated in Opportunistic Networking Environment ONE simulator and analyzed with respect to node density, node mobility, and intermittent connectivity. The results show that Epidemic protocol has moderate average latency, whereas Spray and Wait protocol and MaxProp has better data delivery rate with lesser average latency. Landslides are one of the major natural disasters and an early detection of landslide can be achieved by identifying the landslide triggering vibrations recorded using a geophone network. The major research challenges in this effort are network energy consumption, noise removal and development of a wireless network for transmitting the captured signals.
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This paper presents design and testing of a wireless smart geophone network with enhanced signal processing capability at the site for recording and analyzing geophone signals. The system has the capability to detect landslide induced signals and remove different types of noises produced by footsteps, vehicular movement, rainfall, and stream flow, and transmit the event data to a local processor. For this purpose, a simple and cost effective Arduino based data acquisition system with geophone inputs is developed.
This system helps in reducing the system energy conception and is highly reliable, low cost compared to other traditional systems. This paper mainly focuses on the hardware design of sensor system and algorithms for identifying the characteristics of geophone signals for detecting landslide induced seismic signals. The characteristics of geophone signals for different seismic events recorded by the system are also provided. Due to the increase in the population, human settlement is extending to forest border areas, causing conflicts between elephants and humans, leading to loss of life and property.
Hence, large scale monitoring is required for real- Time detection and warning of elephant intrusion into human settlements. Existing solutions using seismic waves, image processing, etc. The project aims at developing an affordable solution for large-scale monitoring and early warning of elephant intrusion.
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In this work, architecture for elephant intrusion detection using wireless sensor networks is proposed and also a low cost sensor system has been designed and developed after selecting the appropriate sensors for monitoring. After analysing the existing signal processing methods, the most suitable technique for real- Time detection of elephants is chosen and simulated. A two level detection system using microphones and IR sensors is used for monitoring the scenario and sound data is sent using FM transceivers to a PC.
An apparatus reducing power theft on a micro power grid includes a server connected to the micro power grid, the server including a processor, data repository and software executing on the processor from a non-transitory medium the software enabling collection over time of bi-directional current data from smart distribution nodes connected to identified segments of the micro power grid and from smart meters distributed to one or more client demarcation points on the identified segments, processing of the bi-directional current data to determine power theft event frequency and power theft current information, assigning of a class to the individual ones of identified segments according to results of processing, and resetting of the number of packet transmission hop counts between the smart distribution nodes on identified segments and resetting the time period interval between subsequent power theft check routines for each identified segment based upon the classification data.
This paper presents a remote triggered wireless sensor network WSN testbed used to facilitate multi-user remote access to the WSN experiments for virtual learning of wireless sensor network concepts. This testbed provides multiset, multi-group of WSN experimental setup that is capable to provide opportunity to perform remote code editing using over the air programming mechanism. This testbed also provides an intuitive web-based interface to the registered users for running the experiments, accessing and editing the source code of the experiment from anywhere in the world by means of internet.
This remote triggering mechanism offers the user a flexible environment for the experimentation. An experimentation setup of wireless sensor nodes are developed to suit the design of both indoor and outdoor experiments. The outdoor lab setup allows the users to learn the wireless propagational effects in the real environment. The WSN indoor lab setup comprises of nine sensor network experiments which allows the users to learn the WSN concepts such as configuring a WSN, clustering mechanisms, time synchronization mechanisms and experience the practical implementation in real time.
This test bed offers the researchers and students an opportunity to trigger their inquisitiveness by providing the access to remote equipments and materials needed for the experimentation, shared via virtual manner wherein the experiment conduction and output observation can be performed online through an effective visualization tool. The architecture provides a remote code editing mechanism using deluge protocol that offers the user a flexible environment for the experimentation.
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Central and local authentication agents serve a two level security mechanism which makes the system robust to security threats. The lab is accessible for all the students in the world through internet and it will provide an intuitive web-based interface, where registered users can access the code and do code editing. Theft of electricity amounts to 1. Hence there is a great need to detect power thefts in developing nations.
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In this paper, we have proposed a wireless network based infrastructure for power theft detection which caters to other functional requirements of the microgrid such as renewable energy integration, automatic meter reading etc. Algorithm for power theft detection PTDA which is proposed in this paper, works in the distributed intelligent devices of the microgrid infrastructure for power theft detection.
The coordinated action of intelligent devices with PTDA in the microgrid infrastructure enables not only the detection of power theft, but the localization of power theft in the micro-grid. PTDA increases the 1 cost of communication 2 energy consumption of intelligent devices 3 packet latency, if any critical data is piggy backed with power theft data in micro-grid. To solve these issues, we have proposed EPTDNA Efficient Power Theft Data Networking Algorithm which uses the frequency of power theft detection and average power draw for power theft, for the efficient routing of power theft.
Several challenges exist in developing smart buildings such as the development of context aware algorithms and real-time control systems, the integration of numerous sensors to detect various parameters, integration changes in the existing electrical infrastructure, and high cost of deployment.
Another major challenge is to optimize the energy usage in smart buildings without compromising the comfort level of individuals. However, the success of this task requires in depth knowledge of the individual and group behaviour inside the smart building. To solve the aforementioned challenges, we have designed and developed a Smart Personalised System for Energy Management SPSE , a low cost context aware system integrated with personalized and collaborative learning capabilities to understand the real-time behaviour of individuals in a building for optimizing the energy usage in the building.
The context aware system constitutes a wearable device and a wireless switchboard that can continuously monitor several functions such as the real-time monitoring and localization of the presence of the individual, real-time monitoring and detection of the usage of switch board and equipment, and their time of usage by each individual. Using the continuous data collected from the context aware system, personalized and group algorithms can be developed for optimizing the energy usage with minimum sensors.
In this work, the context aware system was tested extensively for module performance and for complete integrated device performance. The study found the proposed system provides the opportunity to collect data necessary for developing a personalized system for smart buildings with minimum sensors. Over the past decade, experimentation for wireless sensor network WSN has been widely used to enrich the learning experience of educators and learners. Our remote triggered WSN laboratory is a multi-set, multi-group, WSN experimental setup that provides an intuitive web-based interface to carry out remote experimentation as well as code editing by registered users.
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This paper presents a multi-level time based scheduling algorithm for our lab which provides optimum utilization, performance and service. Our WSN testbed consists of more than sensor nodes deployed in indoor and outdoor environment. We have implemented and tested two approaches for energy efficiency namely an on demand scheduling and a TDMA based approach which incorporates state transition and CDMA. The paper details the implementation of energy efficiency with dynamic scheduling for our real-time remote triggered WSN.
Our AMRITA remote triggered lab RT Lab for wireless sensor networks WSN offer the students and researchers, an easy, efficient, interactive and user friendly environment to trigger their inquisitiveness by providing them with the sensors, equipments, hardwares and study materials for conducting the lab experiments. RT Lab offers a web-based e-learning platform for the registered users to perform experimentation and coding remotely based on the provided study materials which are shared to them virtually.
The users can learn nesC programming language and conduct the coding by means of the code editing interface.