Distributed Self-Deployment in Visual Sensor Networks

Autonomous decision making in a variety of wireless sensor networks, and also in visual sensor networks (VSNs), specifically, has become a highly researched field in recent years. There is a wide array of applications ranging from military operations to civilian environmental monitoring. To make VSNs highly useful in any type of setting, a number of fundamental problems must be solved, such as sensor node localization, self-deployment, target recognition, etc. This presents a plethora of challenges, as low cost, low energy consumption, and excellent scalability are desired. This thesis describes the design and implementation of a distributed self-deployment method in wireless visual sensor networks. Algorithms are developed for the imple- mentation of both centralized and distributed self-deployment schemes, given a set of randomly placed sensor nodes. In order to self-deploy these nodes, the fundamental problem of localization must first be solved. To this end, visual structured marker detection is utilized to obtain coordinate data in reference to artificial markers, which then is used to deduct the location of a node in an absolute coordinate system. Once localization is complete, the nodes in the VSN are deployed in either centralized or distributed fashion, to pre-defined target locations. As is usually the case, in cen- tralized mode there is a single processing node which makes the vast majority of decisions, and since this one node has knowledge of all events in the VSN, it is able to make optimal decisions, at the expense of time and scalability. The distributed mode, however, offers increased performance in regard to time and scalability, but the final deployment result may be considered sub-optimal. Software is developed for both modes of operations, and a GUI is provided as an easy control interface, which also allows for visualization of the VSN progress in the testing environment. The algorithms are tested on an actual testbed consisting of five custom-built Mobile Sensor Platforms (MSPs). The MSPs are configured to have a camera and an ultra-sonic range sensor. The visual marker detection uses the camera, and for obstacle avoidance during motion, the sonic ranger is used. Eight markers are placed in an area measuring 4 × 4 meters, which is surrounded by white background. Both algorithms are evaluated for speed and accuracy. Experimental results show that localization using the visual markers has an accuracy of about 96% in ideal lighting conditions, and the proposed self-deployment algorithms perform as desired. The MSPs suffer from some physical design limitations, such as lacking wheel encoders for reliable movement in straight lines. Experiments show that over 1 meter of travel the MSPs deviate from the path by an average of 7.5 cm in a lateral direction. Finally, the time needed for each algorithm to complete is recorded, and it is found that centralized and distributed modes require an average of 34.3 and 28.6 seconds, respectively, effectively meaning that distributed self-deployment is approximately 16.5% faster than centralized deployment

Epidural Interventions in the Management of Chronic Spinal Pain: American Society of Interventional Pain Physicians (ASIPP) Comprehensive Evidence-Based Guidelines.

BACKGROUND: Chronic spinal pain is the most prevalent chronic disease with employment of multiple modes of interventional techniques including epidural interventions. Multiple randomized controlled trials (RCTs), observational studies, systematic reviews, and guidelines have been published. The recent review of the utilization patterns and expenditures show that there has been a decline in utilization of epidural injections with decrease in inflation adjusted costs from 2009 to 2018. The American Society of Interventional Pain Physicians (ASIPP) published guidelines for interventional techniques in 2013, and guidelines for facet joint interventions in 2020. Consequently, these guidelines have been prepared to update previously existing guidelines. OBJECTIVE: To provide evidence-based guidance in performing therapeutic epidural procedures, including caudal, interlaminar in lumbar, cervical, and thoracic spinal regions, transforaminal in lumbar spine, and percutaneous adhesiolysis in the lumbar spine. METHODS: The methodology utilized included the development of objective and key questions with utilization of trustworthy standards. The literature pertaining to all aspects of epidural interventions was viewed with best evidence synthesis of available literature and recommendations were provided. RESULTS: In preparation of the guidelines, extensive literature review was performed. In addition to review of multiple manuscripts in reference to utilization, expenditures, anatomical and pathophysiological considerations, pharmacological and harmful effects of drugs and procedures, for evidence synthesis we have included 47 systematic reviews and 43 RCTs covering all epidural interventions to meet the objectives.The evidence recommendations are as follows: Disc herniation: Based on relevant, high-quality fluoroscopically guided epidural injections, with or without steroids, and results of previous systematic reviews, the evidence is Level I for caudal epidural injections, lumbar interlaminar epidural injections, lumbar transforaminal epidural injections, and cervical interlaminar epidural injections with strong recommendation for long-term effectiveness.The evidence for percutaneous adhesiolysis in managing disc herniation based on one high-quality, placebo-controlled RCT is Level II with moderate to strong recommendation for long-term improvement in patients nonresponsive to conservative management and fluoroscopically guided epidural injections. For thoracic disc herniation, based on one relevant, high-quality RCT of thoracic epidural with fluoroscopic guidance, with or without steroids, the evidence is Level II with moderate to strong recommendation for long-term effectiveness.Spinal stenosis: The evidence based on one high-quality RCT in each category the evidence is Level III to II for fluoroscopically guided caudal epidural injections with moderate to strong recommendation and Level II for fluoroscopically guided lumbar and cervical interlaminar epidural injections with moderate to strong recommendation for long-term effectiveness.The evidence for lumbar transforaminal epidural injections is Level IV to III with moderate recommendation with fluoroscopically guided lumbar transforaminal epidural injections for long-term improvement. The evidence for percutaneous adhesiolysis in lumbar stenosis based on relevant, moderate to high quality RCTs, observational studies, and systematic reviews is Level II with moderate to strong recommendation for long-term improvement after failure of conservative management and fluoroscopically guided epidural injections. Axial discogenic pain: The evidence for axial discogenic pain without facet joint pain or sacroiliac joint pain in the lumbar and cervical spine with fluoroscopically guided caudal, lumbar and cervical interlaminar epidural injections, based on one relevant high quality RCT in each category is Level II with moderate to strong recommendation for long-term improvement, with or without steroids. Post-surgery syndrome: The evidence for lumbar and cervical post-surgery syndrome based on one relevant, high-quality RCT with fluoroscopic guidance for caudal and cervical interlaminar epidural injections, with or without steroids, is Level II with moderate to strong recommendation for long-term improvement. For percutaneous adhesiolysis, based on multiple moderate to high-quality RCTs and systematic reviews, the evidence is Level I with strong recommendation for long-term improvement after failure of conservative management and fluoroscopically guided epidural injections. LIMITATIONS: The limitations of these guidelines include a continued paucity of high-quality studies for some techniques and various conditions including spinal stenosis, post-surgery syndrome, and discogenic pain. CONCLUSIONS: These epidural intervention guidelines including percutaneous adhesiolysis were prepared with a comprehensive review of the literature with methodologic quality assessment and determination of level of evidence with strength of recommendations

Appearance-based vehicle localization across seasons in a metric map

Great strides have been made in recent years in developing the necessary technologies to make autonomous cars a reality. However, a number of challenges remain, a major one being that of accurate vehicle localization. This thesis presents a vision-only approach to the outdoor localization problem. The system provides for real-time, metric localization of a moving camera (on a vehicle) in a pre-built 3D map, which is inherently robust with respect to appearance changes. This is achieved by utilizing a novel spatio-temporal map (STM) representation which is built up from multiple drives worth of stereo camera data, as well as a localization algorithm which efficiently retrieves landmarks from the STM to perform appearance-based localization in real-time. The STM encodes the landmark visibility structure of the datasets which were captured to build the map, as well as landmark descriptors and observation times. This visibility structure and meta-data are then exploited for efficient localization. In addition, by splitting the STM up into a number of submaps, computational tractability is ensured during the map-building phase, as well as during localization. Experiments on real data validate that the presented method works better than conventional approaches which operate in a map built of a single dataset.Ph.D