Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

A modified model for the Lobula Giant Movement Detector and its FPGA implementation

The Lobula Giant Movement Detector (LGMD) is a wide-field visual neuron located in the Lobula layer of the Locust nervous system. The LGMD increases its firing rate in response to both the velocity of an approaching object and the proximity of this object. It has been found that it can respond to looming stimuli very quickly and trigger avoidance reactions. It has been successfully applied in visual collision avoidance systems for vehicles and robots. This paper introduces a modified neural model for LGMD that provides additional depth direction information for the movement. The proposed model retains the simplicity of the previous model by adding only a few new cells. It has been simplified and implemented on a Field Programmable Gate Array (FPGA), taking advantage of the inherent parallelism exhibited by the LGMD, and tested on real-time video streams. Experimental results demonstrate the effectiveness as a fast motion detector

Ranging system which compares an object reflected component of a light beam to a reference component of the light beam

A system is described for measuring the distance to an object by comparing a first component of a light pulse that is reflected off the object with a second component of the light pulse that passes along a reference path of known length, which provides great accuracy with a relatively simple and rugged design. The reference path can be changed in precise steps so that it has an equivalent length approximately equal to the path length of the light pulse component that is reflected from the object. The resulting small difference in path lengths can be precisely determined by directing the light pulse components into opposite ends of a detector formed of a material that emits a second harmonic light output at the locations where the opposite going pulses past simultaneously across one another

Coil Gun Turret Control Using A Camera

ABSTRACT --- A conventional weapon usually by pointing to the target aimed by using hands. It is considered less effective and efficient in terms of military service because of spending lots of time to chase the target. So needed a tool to move the weapon automatically. This final project present about object tracking in a weapon and it’s turret, that will be controlled by camera. The camera is used to detect moving targets based on a particular color. In a image sequence consisting of many different objects, accompanied by a different background, this system will be able to distinguish between the target or not. Camera detection is done by taking moving images with color composition that has been determined. Then, The image resolution is resized of the smallest of camera’s resolutions, that is 320x240. Smaller image size are intended for the system’s working to be faster. Capturing image process is use segmentation object process in digital image processing which aims to separate the object region with background. The weapon that will be used, have two degrees of freedom. Maximum 360 degrees rotation in x axis, and maximum 90 degrees in y axis. Both of them using brushed DC motor. At the direction of the y- axis motion required a gear for transmitting power between motor shaft and the shaft, so the shaft is not directly connected to the motor and no distortion. Turret have been designed had four buffers as a solid foundation to bear the entire load. Communication between the camera and weapons carried out by using the cable. Turret will be controlled using the PD control which is expected to reach a position with a quick reference. Key Words: Object tracking, Digital Image Processing, Image sequence, PD (Proposional Deravative) Contro

Evaluation of trackers for Pan-Tilt-Zoom Scenarios

Tracking with a Pan-Tilt-Zoom (PTZ) camera has been a research topic in computer vision for many years. Compared to tracking with a still camera, the images captured with a PTZ camera are highly dynamic in nature because the camera can perform large motion resulting in quickly changing capture conditions. Furthermore, tracking with a PTZ camera involves camera control to position the camera on the target. For successful tracking and camera control, the tracker must be fast enough, or has to be able to predict accurately the next position of the target. Therefore, standard benchmarks do not allow to assess properly the quality of a tracker for the PTZ scenario. In this work, we use a virtual PTZ framework to evaluate different tracking algorithms and compare their performances. We also extend the framework to add target position prediction for the next frame, accounting for camera motion and processing delays. By doing this, we can assess if predicting can make long-term tracking more robust as it may help slower algorithms for keeping the target in the field of view of the camera. Results confirm that both speed and robustness are required for tracking under the PTZ scenario.Comment: 6 pages, 2 figures, International Conference on Pattern Recognition and Artificial Intelligence 201