Overcoming Bandwidth Limitations in Wireless Sensor Networks by Exploitation of Cyclic Signal Patterns: An Event-triggered Learning Approach

Wireless sensor networks are used in a wide range of applications, many of which require real-time transmission of the measurements. Bandwidth limitations result in limitations on the sampling frequency and number of sensors. This problem can be addressed by reducing the communication load via data compression and event-based communication approaches. The present paper focuses on the class of applications in which the signals exhibit unknown and potentially time-varying cyclic patterns. We review recently proposed event-triggered learning (ETL) methods that identify and exploit these cyclic patterns, we show how these methods can be applied to the nonlinear multivariable dynamics of three-dimensional orientation data, and we propose a novel approach that uses Gaussian process models. In contrast to other approaches, all three ETL methods work in real time and assure a small upper bound on the reconstruction error. The proposed methods are compared to several conventional approaches in experimental data from human subjects walking with a wearable inertial sensor network. They are found to reduce the communication load by 60–70%, which implies that two to three times more sensor nodes could be used at the same bandwidth

IDENTIFIKASI UANG KERTAS MENGGUNAKAN METODE BACKPROPAGASI PADA SISTEM INTERNET-TELEPON UMUM

Now a days, the communication device is being a part of the human lifestyles. In every activity, the communication device either cellphones or fixed phone being a primary device to doing a telecomunication. In addition voices communication, data communication via internet can�t be separated from public. In this final project designed a system that combine between voices communication and data communication with the concept of public internet-telephony. In this final project, will be designed a system to identify money by using an artificial neural networks algorithms (ANN) with backpropagasi. This system will be used to authenticate the public internet telephony billing system. System will recognize the contours of money with several sensors that are installed, then the data will be training using ANN backpropagation method and stored as a reference data to identify money With this final project , the peoples will get a public facility to sustain the needs in modern era, both voice and data in the internet. Key words: Artificial neural network, backpropagation, public telephony internet , currency paper

Control of Networked Robotic Systems

With the infrastructure of ubiquitous networks around the world, the study of robotic systems over communication networks has attracted widespread attention. This area is denominated as networked robotic systems. By exploiting the fruitful technological developments in networking and computing, networked robotic systems are endowed with potential and capabilities for several applications. Robots within a network are capable of connecting with control stations, human operators, sensors, and other robots via digital communication over possibly noisy channels/media. The issues of time delays in communication and data losses have emerged as a pivotal issue that have stymied practical deployment. The aim of this dissertation is to develop control algorithms and architectures for networked robotic systems that guarantee stability with improved overall performance in the presence of time delays in communication. The first topic addressed in this dissertation is controlled synchronization that is utilized for networked robotic systems to achieve collective behaviors. Exploiting passivity property of individual robotic systems, the proposed control schemes and interconnections are shown to ensure stability and convergence of synchronizing errors. The robustness of the control algorithms to constant and time-varying communication delays is also studied. In addition to time delays, the number of communication links, which prevents scalability of networked robotic systems, is another challenging issue. Thus, a synchronizing control with practically feasible constraints of network topology is developed. The problem of networked robotic systems interacting with human operators is then studied subsequently. This research investigates a teleoperation system with heterogeneous robots under asymmetric and unknown communication delays. Sub-task controllers are proposed for redundant slave robot to autonomously achieve additional tasks, such as singularity avoidance, joint angle limits, and collision avoidance. The developed control algorithms can enhance the efficiency of teleoperation systems, thereby ameliorating the performance degradation due to cognitive limitations of human operator and incomplete information about the environment. Compared to traditional robotic systems, control of robotic manipulators over networks has significant advantages; for example, increased flexibility and ease of maintenance. With the utilization of scattering variables, this research demonstrates that transmitting scattering variables over delayed communications can stabilize an otherwise unstable system. An architecture utilizing delayed position feedback in conjunction with scattering variables is developed for the case of time-varying communication delays. The proposed control architecture improves tracking performance and stabilizes robotic manipulators with input-output communication delays. The aforementioned control algorithms and architectures for networked robotic systems are validated via numerical examples and experiments

Sensorless sensing with WiFi

Abstract: Can WiFi signals be used for sensing purpose? The growing PHY layer capabilities of WiFi has made it possible to reuse WiFi signals for both communication and sensing. Sensing via WiFi would enable remote sensing without wearable sensors, simultaneous perception and data transmission without extra communication infrastructure, and contactless sensing in privacy-preserving mode. Due to the popularity of WiFi devices and the ubiquitous deployment of WiFi networks, WiFi-based sensing networks, if fully connected, would potentially rank as one of the world’s largest wireless sensor networks. Yet the concept of wireless and sensorless sensing is not the simple combination of WiFi and radar. It seeks breakthroughs from dedicated radar systems, and aims to balance between low cost and high accuracy, to meet the rising demand for pervasive environment perception in everyday life. Despite increasing research interest, wireless sensing is still in its infancy. Through introductions on basic principles and working prototypes, we review the feasibilities and limitations of wireless, sensorless, and contactless sensing via WiFi. We envision this article as a brief primer on wireless sensing for interested readers to explore this open and largely unexplored field and create next-generation wireless and mobile computing applications. Key words: Channel State Information (CSI); sensorless sensing; WiFi; indoor localization; device-free human detection; activity recognition; wireless networks; ubiquitous computing

(R)Urban synergy reconsidered: the role of information networks in climate change adaptation and mitigation

The paper is focused on the relationship between urban and rural settlements, established via information networks and oriented towards climate change adaptation and mitigation. The first part of the paper provides a review of emerging ideas and innovations related to the (un)conventional use of information networks in reducing the consequences of climate change, while the second part examines the strategic role of networks in the exchange of data and knowledge. Two levels are especially emphasized - the domain of public communication of climate change, and the level of connectivity within (r)urban hybrid systems (i.e. their effectiveness, accessibility and low-carbon outcomes). In accordance with recent environmental and technological trends, as well as the possible spatiofunctional flexibility of (r)urban hybrid settlements, the paper indentifies and analyses three areas of networks applicability, targeting main challenges of the anticipated climate-friendly development - human behaviour, ecological awareness and general efficiency

Real life Applications of Internet of Things

The Internet of Things is the next technological revolution after the revolution of computer and internet. IoT integrates the new technologies of computing and communication (e.g. Sensor networks, RFID, Mobile communication and IPV6 etc). The Internet of Things is an emerging topic of technical, social, and economic significance. The term Internet of Things generally refers to scenarios where network connectivity and computing capability extends to objects, sensors and everyday items not normally considered computers, allowing these devices to generate exchange and consume data with minimal human intervention. Internet connect “all people”, Internet of Things connect “all things”. Interconnection of Things or Objects or Machines, e.g., sensors, actuators, mobile phones, electronic devices, home appliances, any existing items and interact with each other via Interne

cPath: open source software for collecting, storing, and querying biological pathways

BACKGROUND: Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required. RESULTS: We have developed cPath, an open source database and web application for collecting, storing, and querying biological pathway data. cPath makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Key features include: a built-in identifier mapping service for linking identical interactors and linking to external resources; built-in support for PSI-MI and BioPAX standard pathway exchange formats; a web service interface for searching and retrieving pathway data sets; and thorough documentation. The cPath software is freely available under the LGPL open source license for academic and commercial use. CONCLUSION: cPath is a robust, scalable, modular, professional-grade software platform for collecting, storing, and querying biological pathways. It can serve as the core data handling component in information systems for pathway visualization, analysis and modeling