Resource Optimization in Wireless Sensor Networks for an Improved Field Coverage and Cooperative Target Tracking

There are various challenges that face a wireless sensor network (WSN) that mainly originate from the limited resources a sensor node usually has. A sensor node often relies on a battery as a power supply which, due to its limited capacity, tends to shorten the life-time of the node and the network as a whole. Other challenges arise from the limited capabilities of the sensors/actuators a node is equipped with, leading to complication like a poor coverage of the event, or limited mobility in the environment. This dissertation deals with the coverage problem as well as the limited power and capabilities of a sensor node. In some environments, a controlled deployment of the WSN may not be attainable. In such case, the only viable option would be a random deployment over the region of interest (ROI), leading to a great deal of uncovered areas as well as many cutoff nodes. Three different scenarios are presented, each addressing the coverage problem for a distinct purpose. First, a multi-objective optimization is considered with the purpose of relocating the sensor nodes after the initial random deployment, through maximizing the field coverage while minimizing the cost of mobility. Simulations reveal the improvements in coverage, while maintaining the mobility cost to a minimum. In the second scenario, tracking a mobile target with a high level of accuracy is of interest. The relocation process was based on learning the spatial mobility trends of the targets. Results show the improvement in tracking accuracy in terms of mean square position error. The last scenario involves the use of inverse reinforcement learning (IRL) to predict the destination of a given target. This lay the ground for future exploration of the relocation problem to achieve improved prediction accuracy. Experiments investigated the interaction between prediction accuracy and terrain severity. The other WSN limitation is dealt with by introducing the concept of sparse sensing to schedule the measurements of sensor nodes. A hybrid WSN setup of low and high precision nodes is examined. Simulations showed that the greedy algorithm used for scheduling the nodes, realized a network that is more resilient to individual node failure. Moreover, the use of more affordable nodes stroke a better trade-off between deployment feasibility and precision

Location prediction optimisation in WSNs using kriging interpolation

© The Institution of Engineering and Technology 2016. Many wireless sensor network (WSN) applications rely on precise location or distance information. Despite the potentials of WSNs, efficient location prediction is one of the subsisting challenges. This study presents novel prediction algorithms based on a Kriging interpolation technique. Given that each sensor is aware of its location only, the aims of this work are to accurately predict the temperature at uncovered areas and estimate positions of heat sources. By taking few measurements within the field of interest and by using Kriging interpolation to iteratively enhance predictions of temperature and location of heat sources in uncovered regions, the degree of accuracy is significantly improved. Following a range of independent Monte Carlo runs in different experiments, it is shown through a comparative analysis that the proposed algorithm delivers approximately 98% prediction accuracy

VLTI status update: a decade of operations and beyond

We present the latest update of the European Southern Observatory's Very Large Telescope interferometer (VLTI). The operations of VLTI have greatly improved in the past years: reduction of the execution time; better offering of telescopes configurations; improvements on AMBER limiting magnitudes; study of polarization effects and control for single mode fibres; fringe tracking real time data, etc. We present some of these improvements and also quantify the operational improvements using a performance metric. We take the opportunity of the first decade of operations to reflect on the VLTI community which is analyzed quantitatively and qualitatively. Finally, we present briefly the preparatory work for the arrival of the second generation instruments GRAVITY and MATISSE.Comment: 10 pages, 7 figures, Proceedings of the SPIE, 9146-1

Evaluation of cervical proprioceptive function: optimizing protocols and comparison between tests in normal subjects

STUDY DESIGN: A test-retest design evaluated stability as well as within and between day reliability. \ud \ud OBJECTIVE: The study aimed to define optimum protocols for the cervical joint position error (JPE) and cervicocephalic kinesthesia tests and to investigate association between performances in the tests. \ud \ud SUMMARY OF BACKGROUND DATA: The cervical JPE and cervicocephalic kinesthesia tests are proposed as measures of cervical proprioception. However, there has been little investigation of the number of trials needed to obtain stable and reliable estimates of performance. Both tests have potential limitations in reflecting the underlying construct of cervical proprioception and association between performances in both has not been investigated previously. \ud \ud METHODS: Head repositioning and head-tracking errors were measured using an electromagnetic-tracking system in 16 normal subjects, tested on 3 occasions over 2 days. The effect of different numbers of trial repeats was analyzed descriptively in terms of stability of measures obtained and by using intraclass correlation coefficients to assess reliability. Association between the tests was analyzed with the Pearson correlation coefficient. \ud \ud RESULTS: Stable estimates of performance were obtained when data from 6 or more trials was included. The greatest test-retest reliability was obtained with 5 or more trials in both the cervical JPE (intraclass correlation coefficients = 0.73-0.84) and cervicocephalic kinesthesia (intraclass correlation coefficients = 0.90-0.97) tests. Correlation analyses indicated no significant association between performances in the 2 tests (r = -0.476-0.228, P > 0.05). \ud \ud CONCLUSION: Our finding that at least 6 trials were needed to optimize stability, and reliability of outcome measures has important implications for application of these tests. The lack of correlation between performances in the tests supports the suggestion that they are not comparable measures of cervical proprioception. Further planned studies will include a range of tests challenging different aspects of cervical proprioceptive contribution to sensorimotor control in different subcategories of neck pain patients

Active Estimation of Distance in a Robotic Vision System that Replicates Human Eye Movement

Many visual cues, both binocular and monocular, provide 3D information. When an agent moves with respect to a scene, an important cue is the different motion of objects located at various distances. While a motion parallax is evident for large translations of the agent, in most head/eye systems a small parallax occurs also during rotations of the cameras. A similar parallax is present also in the human eye. During a relocation of gaze, the shift in the retinal projection of an object depends not only on the amplitude of the movement, but also on the distance of the object with respect to the observer. This study proposes a method for estimating distance on the basis of the parallax that emerges from rotations of a camera. A pan/tilt system specifically designed to reproduce the oculomotor parallax present in the human eye was used to replicate the oculomotor strategy by which humans scan visual scenes. We show that the oculomotor parallax provides accurate estimation of distance during sequences of eye movements. In a system that actively scans a visual scene, challenging tasks such as image segmentation and figure/ground segregation greatly benefit from this cue.National Science Foundation (BIC-0432104, CCF-0130851

Scheduling for Multi-Camera Surveillance in LTE Networks

Wireless surveillance in cellular networks has become increasingly important, while commercial LTE surveillance cameras are also available nowadays. Nevertheless, most scheduling algorithms in the literature are throughput, fairness, or profit-based approaches, which are not suitable for wireless surveillance. In this paper, therefore, we explore the resource allocation problem for a multi-camera surveillance system in 3GPP Long Term Evolution (LTE) uplink (UL) networks. We minimize the number of allocated resource blocks (RBs) while guaranteeing the coverage requirement for surveillance systems in LTE UL networks. Specifically, we formulate the Camera Set Resource Allocation Problem (CSRAP) and prove that the problem is NP-Hard. We then propose an Integer Linear Programming formulation for general cases to find the optimal solution. Moreover, we present a baseline algorithm and devise an approximation algorithm to solve the problem. Simulation results based on a real surveillance map and synthetic datasets manifest that the number of allocated RBs can be effectively reduced compared to the existing approach for LTE networks.Comment: 9 pages, 10 figure

Multimodal Signal Processing and Learning Aspects of Human-Robot Interaction for an Assistive Bathing Robot

We explore new aspects of assistive living on smart human-robot interaction (HRI) that involve automatic recognition and online validation of speech and gestures in a natural interface, providing social features for HRI. We introduce a whole framework and resources of a real-life scenario for elderly subjects supported by an assistive bathing robot, addressing health and hygiene care issues. We contribute a new dataset and a suite of tools used for data acquisition and a state-of-the-art pipeline for multimodal learning within the framework of the I-Support bathing robot, with emphasis on audio and RGB-D visual streams. We consider privacy issues by evaluating the depth visual stream along with the RGB, using Kinect sensors. The audio-gestural recognition task on this new dataset yields up to 84.5%, while the online validation of the I-Support system on elderly users accomplishes up to 84% when the two modalities are fused together. The results are promising enough to support further research in the area of multimodal recognition for assistive social HRI, considering the difficulties of the specific task. Upon acceptance of the paper part of the data will be publicly available