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Optimal coverage multi-path scheduling scheme with multiple mobile sinks for WSNs
Wireless Sensor Networks (WSNs) are usually formed with many tiny sensors which are randomly deployed within sensing field for target monitoring. These sensors can transmit their monitored data to the sink in a multi-hop communication manner. However, the âhot spotsâ problem will be caused since nodes near sink will consume more energy during forwarding. Recently, mobile sink based technology provides an alternative solution for the long-distance communication and sensor nodes only need to use single hop communication to the mobile sink during data transmission. Even though it is difficult to consider many network metrics such as sensor position, residual energy and coverage rate etc., it is still very important to schedule a reasonable moving trajectory for the mobile sink. In this paper, a novel trajectory scheduling method based on coverage rate for multiple mobile sinks (TSCR-M) is presented especially for large-scale WSNs. An improved particle swarm optimization (PSO) combined with mutation operator is introduced to search the parking positions with optimal coverage rate. Then the genetic algorithm (GA) is adopted to schedule the moving trajectory for multiple mobile sinks. Extensive simulations are performed to validate the performance of our proposed method
NFC Sensors Based on Energy Harvesting for IoT Applications
The availability of low-cost near-field communication (NFC) devices, the incorporation of NFC readers into most current mobile phones, and the inclusion of energy-harvesting (EH) capabilities in NFC chips make NFC a key technology for the development of green Internet of Things (IoT) applications. In this chapter, an overview of recent advances in the field of battery-less NFC sensors at 13.56Â MHz is provided, and a comparison to other short-range RFID technologies is given. After reviewing power transfer in NFC, recommendations for the practical design of NFC-based sensor tags and NFC readers are made. A list of commercial NFC integrated circuits with energy-harvesting capabilities is also provided. A survey of recent battery-less NFC sensors developed by the group including soil moisture, water content, pH, color, and implanted NFC sensors is done
Technical Report: Cooperative Multi-Target Localization With Noisy Sensors
This technical report is an extended version of the paper 'Cooperative
Multi-Target Localization With Noisy Sensors' accepted to the 2013 IEEE
International Conference on Robotics and Automation (ICRA).
This paper addresses the task of searching for an unknown number of static
targets within a known obstacle map using a team of mobile robots equipped with
noisy, limited field-of-view sensors. Such sensors may fail to detect a subset
of the visible targets or return false positive detections. These measurement
sets are used to localize the targets using the Probability Hypothesis Density,
or PHD, filter. Robots communicate with each other on a local peer-to-peer
basis and with a server or the cloud via access points, exchanging measurements
and poses to update their belief about the targets and plan future actions. The
server provides a mechanism to collect and synthesize information from all
robots and to share the global, albeit time-delayed, belief state to robots
near access points. We design a decentralized control scheme that exploits this
communication architecture and the PHD representation of the belief state.
Specifically, robots move to maximize mutual information between the target set
and measurements, both self-collected and those available by accessing the
server, balancing local exploration with sharing knowledge across the team.
Furthermore, robots coordinate their actions with other robots exploring the
same local region of the environment.Comment: Extended version of paper accepted to 2013 IEEE International
Conference on Robotics and Automation (ICRA
The Applicability of Ambient Sensors as Proximity Evidence for NFC Transactions
Near Field Communication (NFC) has enabled mobile phones to emulate contactless smart cards. Similar to contactless smart cards, they are also susceptible to relay attacks. To counter these, a number of methods have been proposed that rely primarily on ambient sensors as a proximity detection mechanism (also known as an anti-relay mechanism). In this paper, we empirically evaluate a comprehensive set of ambient sensors for their effectiveness as a proximity detection mechanism for NFC contactless-based applications like banking, transport and high-security access controls. We selected 17 sensors available via the Google Android platform. Each sensor, where feasible, was used to record the measurements of 1,000 contactless transactions at four different physical locations. A total of 252 users, a random sample from the university student population, were involved during the field trials. After careful analysis, we conclude that no single evaluated mobile ambient sensor is suitable for proximity detection in NFC-based contactless applications in realistic deployment scenarios. Lastly, we identify a number of potential avenues that may improve their effectiveness
Use of Multi-Spectral High Repetition Rate LED Systems for High Bandwidth Underwater Optical Communications, and Communications to Surface and Aerial Systems
A variety of both existing and developing sensors would benefit from near real time communication of high bandwidth data. To cite just one example, sensors that could more accurately report real-time positions of marine mammals would be useful in reducing whale-ship collisions. Similar considerations are relevant for maritime port and harbor security, including detection and alerts for divers or autonomous underwater vehicles (AUVs) that could pose a risk to ships. Especially in ports and harbors, field experiments have confirmed that acoustic communication in these cluttered and noisy shallow water environments, compounded with vertical reflecting surfaces formed by piers and pilings, can limit the reliability and utility of underwater acoustic communications. Moreover, many sensors have greater bandwidth requirements than acoustic communications are able to provide. We here discuss the development of high repetition rate multispectral LED optical systems initially developed for imaging, but also capable of simultaneous data transmission at rates of approximately100 kilobits per second. Results are discussed for the multispectral images from coral reefs in Guam, and data transmission experiments from underwater to surface vessels. Subsequent field efforts will extend data transmission from AUVs to unmanned aircraft systems (UAS)
Communication system for a tooth-mounted RF sensor used for continuous monitoring of nutrient intake
In this Thesis, the communication system of a wearable device that monitors the userâs diet is studied. Based in a novel RF metamaterial-based mouth sensor, different decisions have to be made concerning the systemâs technologies, such as the power source options for the device, the wireless technology used for communications and the method to obtain data from the sensor. These issues, along with other safety rules and regulations, are reviewed, as the first stage of development of the Food-Intake Monitoring projectOutgoin
Near-Optimal Sensor Scheduling for Batch State Estimation: Complexity, Algorithms, and Limits
In this paper, we focus on batch state estimation for linear systems. This
problem is important in applications such as environmental field estimation,
robotic navigation, and target tracking. Its difficulty lies on that limited
operational resources among the sensors, e.g., shared communication bandwidth
or battery power, constrain the number of sensors that can be active at each
measurement step. As a result, sensor scheduling algorithms must be employed.
Notwithstanding, current sensor scheduling algorithms for batch state
estimation scale poorly with the system size and the time horizon. In addition,
current sensor scheduling algorithms for Kalman filtering, although they scale
better, provide no performance guarantees or approximation bounds for the
minimization of the batch state estimation error. In this paper, one of our
main contributions is to provide an algorithm that enjoys both the estimation
accuracy of the batch state scheduling algorithms and the low time complexity
of the Kalman filtering scheduling algorithms. In particular: 1) our algorithm
is near-optimal: it achieves a solution up to a multiplicative factor 1/2 from
the optimal solution, and this factor is close to the best approximation factor
1/e one can achieve in polynomial time for this problem; 2) our algorithm has
(polynomial) time complexity that is not only lower than that of the current
algorithms for batch state estimation; it is also lower than, or similar to,
that of the current algorithms for Kalman filtering. We achieve these results
by proving two properties for our batch state estimation error metric, which
quantifies the square error of the minimum variance linear estimator of the
batch state vector: a) it is supermodular in the choice of the sensors; b) it
has a sparsity pattern (it involves matrices that are block tri-diagonal) that
facilitates its evaluation at each sensor set.Comment: Correction of typos in proof
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