Academic literature on the topic 'Autonomous surveillance'

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Journal articles on the topic "Autonomous surveillance"

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Nair, Mohnish P. "Autonomous Surveillance Robot (ASaR)." International Journal for Research in Applied Science and Engineering Technology 8, no. 7 (July 31, 2020): 531–39. http://dx.doi.org/10.22214/ijraset.2020.30298.

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Jurdak, Raja, Alberto Elfes, Branislav Kusy, Ashley Tews, Wen Hu, Emili Hernandez, Navinda Kottege, and Pavan Sikka. "Autonomous surveillance for biosecurity." Trends in Biotechnology 33, no. 4 (April 2015): 201–7. http://dx.doi.org/10.1016/j.tibtech.2015.01.003.

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Shoro, Ghulam Mustafa. "Design of UAV Autonomous Charging Pad for Surveillance." Revista Gestão Inovação e Tecnologias 11, no. 3 (June 30, 2021): 1552–61. http://dx.doi.org/10.47059/revistageintec.v11i3.2030.

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Lo, Li-Yu, Chi Hao Yiu, Yu Tang, An-Shik Yang, Boyang Li, and Chih-Yung Wen. "Dynamic Object Tracking on Autonomous UAV System for Surveillance Applications." Sensors 21, no. 23 (November 27, 2021): 7888. http://dx.doi.org/10.3390/s21237888.

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The ever-burgeoning growth of autonomous unmanned aerial vehicles (UAVs) has demonstrated a promising platform for utilization in real-world applications. In particular, a UAV equipped with a vision system could be leveraged for surveillance applications. This paper proposes a learning-based UAV system for achieving autonomous surveillance, in which the UAV can be of assistance in autonomously detecting, tracking, and following a target object without human intervention. Specifically, we adopted the YOLOv4-Tiny algorithm for semantic object detection and then consolidated it with a 3D object pose estimation method and Kalman filter to enhance the perception performance. In addition, UAV path planning for a surveillance maneuver is integrated to complete the fully autonomous system. The perception module is assessed on a quadrotor UAV, while the whole system is validated through flight experiments. The experiment results verified the robustness, effectiveness, and reliability of the autonomous object tracking UAV system in performing surveillance tasks. The source code is released to the research community for future reference.
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Kadam, Nilesh. "Autonomous Real Time Surveillance System." IOSR Journal of Engineering 03, no. 03 (March 2013): 22–25. http://dx.doi.org/10.9790/3021-03332225.

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Mensah, Daniel Antwi, and Emmanuel Djaba. "Autonomous Road Crossing Surveillance System." Advances in Multidisciplinary and scientific Research Journal Publication 29 (December 15, 2021): 171–78. http://dx.doi.org/10.22624/aims/abmic2021-v2-p13.

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Accidents related with vulnerable pedestrians around crosswalks are continued so that proactive safety support system is required. Pedestrian detection from frames captured by a camera is a significant and yet challenging task. An autonomous road crossing surveillance system would be ideal for tracking pedestrians who want to cross the road and assist them. A practical solution for aiding pedestrians regularly, a road crossing surveillance with real-time Pedestrian Detection. Since the background subtraction from videos and images is still a persistent problem and difficult to accomplish. A Haar Cascade Classifier with the full-body detection algorithm is used to detect people in real-time captured by a camera. Keywords: Pedestrian crossing, surveillance, road crossing surveillance, surveillance system, autonomous, Haar Cascade Classifier.
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Abdul- Samed, Baqir Nasser. "Oil Facilities Surveillance Using an Autonomous Quadrotor." Journal of Petroleum Research and Studies 12, no. 1(Suppl.) (April 21, 2022): 211–24. http://dx.doi.org/10.52716/jprs.v12i1(suppl.).633.

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This work addresses using the autonomous quadrotor or unmanned aerial vehicle (UAV) for surveillance of oil fields, Facilities and pipelines since that can be very costly and dangerous specially in dangerous zones. This topic is very important because of the money consuming to repair and protect these oil facilities. Quadrotors are very small Vertical take-off landing (VTOL) helicopter, cheap, easy to use and has many other fields of applications. Quadrotor’s dynamic model involves nonlinearity, uncertainties, and coupling which makes the Quadrotor has a very complex system. PID controllers are proposed for controlling the quadrotor altitude through different environments during different missions. To drive the quadrotor to follow the desired trajectory pure pursuit algorithm (PPA) will be use. The simulation results will be pretested using the visual simulator named Gazebo with the aid of ROS to connected with the MATLAB to show the movement of the quadrotor insides different environments.
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Unlu, Eren, Emmaneul Zenou, Nicolas Riviere, and Paul-Edouard Dupouy. "An autonomous drone surveillance and tracking architecture." Electronic Imaging 2019, no. 15 (January 13, 2019): 35–1. http://dx.doi.org/10.2352/issn.2470-1173.2019.15.avm-035.

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Hannon, S. M. "Autonomous infrared doppler radar: Airport surveillance applications." Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere 25, no. 10-12 (January 2000): 1005–11. http://dx.doi.org/10.1016/s1464-1909(00)00143-x.

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Lee, Min-Fan Ricky, and Zhih-Shun Shih. "Autonomous Surveillance for an Indoor Security Robot." Processes 10, no. 11 (October 24, 2022): 2175. http://dx.doi.org/10.3390/pr10112175.

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Conventional surveillance for a security robot suffers from severe limitations, perceptual aliasing (e.g., different places/objects can appear identical), occlusion (e.g., place/object appearance changes between visits), illumination changes, significant viewpoint changes, etc. This paper proposes an autonomous robotic system based on CNN (convolutional neural network) to perform visual perception and control tasks. The visual perception aims to identify all objects moving in the scene and to verify whether the target is an authorized person. The visual perception system includes a motion detection module, a tracking module, face detection, and a recognition module. The control system includes motion control and navigation (path planning and obstacle avoidance). The empirical validation includes the evaluation metrics, such as model speed, accuracy, precision, recall, ROC (receiver operating characteristic) curve, P-R (precision–recall) curve, F1-score for AlexNet, VggNet, and GoogLeNet, and RMSE (root-mean-square error) value of mapping errors. The experimental results showed that the average accuracy of VggNet under four different illumination changes is 0.95, and it has the best performance under all unstable factors among three CNN architectures. For the accuracy of building maps in real scenes, the mapping error is 0.222 m.
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Dissertations / Theses on the topic "Autonomous surveillance"

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Johannsson, Hordur. "Toward autonomous harbor surveillance." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/60167.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
Includes bibliographical references (p. 105-113).
In this thesis we address the problem of drift-free navigation for underwater vehicles performing harbor surveillance and ship hull inspection. Maintaining accurate localization for the duration of a mission is important for a variety of tasks, such as planning the vehicle trajectory and ensuring coverage of the area to be inspected. Our approach uses only onboard sensors in a simultaneous localization and mapping setting and removes the need for any external infrastructure like acoustic beacons. We extract dense features from a forward-looking imaging sonar and apply pair-wise registration between sonar frames. The registrations are combined with onboard velocity, attitude and acceleration sensors to obtain an improved estimate of the vehicle trajectory. In addition, an architecture for a persistent mapping is proposed. With the intention of handling long term operations and repetitive surveillance tasks. The proposed architecture is flexible and supports different types of vehicles and mapping methods. The design of the system is demonstrated with an implementation of some of the key features of the system. In addition, methods for re-localization are considered. Finally, results from several experiments that demonstrate drift-free navigation in various underwater environments are presented.
by Hordur Johannsson.
S.M.
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Oliver, John Douglas. "Autonomous surveillance in an urban environment." Thesis, University of Warwick, 2009. http://wrap.warwick.ac.uk/3183/.

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A number of algorithms have been developed in the past for the purposes of target tracking, these have generally been for simple polygonal environments. However as the technology for autonomous vehicles develops for use in the real world these tracking algorithms need to be tested in larger more realistic environments. This work investigates the use of tracking algorithms to control a team of road based robotic platforms, tracking pedestrian targets in urban environments. The novelty of this work is in the identification of the aspects of the environment that affect target tracking algorithms, and modifying the algorithms to cope with them. Problems such as the frequent stalemates reached as an algorithms movement is limited by the highly restricted movement space or the identification of “short cuts” in which the target can take much shorter routes between positions than the robots. Algorithms are developed that overcome these limitations and they are tested in a simulation that is an accurate representation of a real environment. The algorithms are partly based on existing work and are developed extensively to be suitable for the environment. These algorithms are tested for their ability to maintain visual contact with the target. The scenario is tested with varying numbers of robots, speeds and locations. Three algorithms were developed and tested, one built as an extension of existing target tracking algorithms (Combined Urban Tracker) and another two algorithms developed specifically for this environment (Short Cut Path, and Branch). It is concluded that the Combined Urban Tracker and Short Cut Path algorithms performed comparably with a less than 0:3% difference in performance between the two both averaging roughly 54% effectiveness overall, however the Branch algorithm fared significantly worse averaging only 43% overall. The areas within the environment that give significant problems are large open spaces and areas that are significantly occluded from the road network. This work provides a platform on which further development in this area can be based in order to progress tracking algorithms towards being of practical use.
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Oh, Hyondong. "Towards autonomous surveillance and tracking by multiple UAVs." Thesis, Cranfield University, 2013. http://dspace.lib.cranfield.ac.uk/handle/1826/8266.

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This research investigates the use of small and low-cost UAVs (Unmanned Aerial Vehicles) for autonomous aerial surveillance, which aims to identify and continuously track suspicious vehicles and disguised threats in the ground traffic. Since typical ground traffic in an urban environment is quite dense and involves numerous vehicles, achieving this surveillance capability by a single mobile plat¬form is unlikely to be feasible in many aspects. In particular, due to physical constraints, it might be difficult for one UAV to cover large areas simultaneously, which is often critical to mission success in a rapidly changing environment. Be¬sides, in order to obtain accurate information of ground traffic, a single UAV platform will need to rely on sensors which are expensive yet vulnerable to the failure of the platform or sensing block by obstacles. Using multiple UAVs with relatively cheap aboard sensors with information fusion techniques enhancing sensing accuracy could resolve above issues of a single platform without signifi¬cantly increasing an operational cost. Therefore, this thesis deals with the surveillance application of multiple air¬borne sensor platforms endowed with an appropriate level of autonomous de¬cision making to support human operators. A group of UAVs become multiple mobile sensor platforms, and tasks/routes of each UAV need to be efficiently and optimally planned to cooperatively achieve mission objectives. Efficient and sophisticated algorithms for data acquisition/analysis, information fusion, path planning and formation reconfiguration ensuring feasible and safe cooperation, and decision making for cooperative missions are essentially to be developed, in order to take advantage of multiple aerial sensing sources for surveillance. Among various techniques for autonomous surveillance as listed above, this the¬sis seeks to develop and (partly) integrate some of important components: search route planning, behaviour identification/recognition, and moving target tracking, while examining benefits and drawbacks of using multiple UAVs. A particular focus is on multi-sensor management and information fusion in consideration of physical constraints of the platform and strict real-time requirements of the applications in uncertain and dynamic environments. This research investigates the use of small and low-cost UAVs (Unmanned Aerial Vehicles) for autonomous aerial surveillance, which aims to identify and continuously track suspicious vehicles and disguised threats in the ground traffic. Since typical ground traffic in an urban environment is quite dense and involves numerous vehicles, achieving this surveillance capability by a single mobile plat-form is unlikely to be feasible in many aspects. In particular, due to physical constraints, it might be difficult for one UAV to cover large areas simultaneously, which is often critical to mission success in a rapidly changing environment. Be-sides, in order to obtain accurate information of ground traffic, a single UAV platform will need to rely on sensors which are expensive yet vulnerable to the failure of the platform or sensing block by obstacles. Using multiple UAVs with relatively cheap aboard sensors with information fusion techniques enhancing sensing accuracy could resolve above issues of a single platform without signifi-cantly increasing an operational cost. Therefore, this thesis deals with the surveillance application of multiple air-borne sensor platforms endowed with an appropriate level of autonomous de-cision making to support human operators. A group of UAVs become multiple mobile sensor platforms, and tasks/routes of each UAV need to be efficiently and optimally planned to cooperatively achieve mission objectives. Efficient and sophisticated algorithms for data acquisition/analysis, information fusion, path planning and formation reconfiguration ensuring feasible and safe cooperation, and decision making for cooperative missions are essentially to be developed, in order to take advantage of multiple aerial sensing sources for surveillance. Among various techniques for autonomous surveillance as listed above, this the¬sis seeks to develop and (partly) integrate some of important components: search route planning, behaviour identification/recognition, and moving target tracking, while examining benefits and drawbacks of using multiple UAVs. A particular focus is on multi-sensor management and information fusion in consideration of physical constraints of the platform and strict real-time requirements of the applications in uncertain and dynamic environments. This thesis firstly proposes a road-network search planning algorithm by which UAVs are able to efficiently patrol every road identified in the map. A mixed integer linear programming problem (MILP) is formulated to find an optimal so¬lution minimising a total flight time, while accommodating physical constraints of the UAV with the Dubins path. To overcome the computational burden of the MILP, an approximation approach is also proposed. By running Monte Carlo sim¬ulation with the randomly generated maps, an efficient UAV team size and path planning method is examined. Secondly, this thesis proposes a behaviour recog¬nition methodology for ground vehicles moving within road traffic to identify abnormal behaviour. Ground vehicle behaviour is first classified into represen¬tative driving modes, and string pattern matching theory is applied to detect suspicious behaviours in the driving mode history. Moreover, a fuzzy decision making process is developed to systematically exploit all available information obtained from a complex environment considering spatiotemporal environment factors as well as several aspects of behaviours. Lastly, to achieve continuous tracking of detected suspicious vehicles for closer and higher-resolution surveil¬lance data, this thesis proposes several coordinated standoff tracking guidance algorithms using multiple UAVs. The effect of the improved target estimation accuracy on the tracking guidance performance is also examined using roadmap information and sensor fusion techniques. From this thesis, it can be identified that following aspects need to be carefully considered to realise autonomous surveillance using multiple UAVs: i) how many UAVs/sensors would be enough to perform a mission in terms of efficiency, es¬timation accuracy and guidance performance, ii) information gathered by UAVs only is enough, or domain knowledge (local context and past experience) might be additionally required, iii) communication structure between UAVs, and iv) com¬putation time. The proposed autonomous surveillance system utilising multiple UAVs is expected to greatly increase the amount of area that can be continuously monitored, while reducing the number of human operators and their workload required to analyse surveillance data and respond to identified targets.
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Cowling, Michael, and n/a. "Non-Speech Environmental Sound Classification System for Autonomous Surveillance." Griffith University. School of Information Technology, 2004. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20040428.152425.

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Sound is one of a human beings most important senses. After vision, it is the sense most used to gather information about the environment. Despite this, comparatively little research has been done into the field of sound recognition. The research that has been done mainly centres around the recognition of speech and music. Our auditory environment is made up of many sounds other than speech and music. This sound information can be taped into for the benefit of specific applications such as security systems. Currently, most researchers are ignoring this sound information. This thesis investigates techniques to recognise environmental non-speech sounds and their direction, with the purpose of using these techniques in an autonomous mobile surveillance robot. It also presents advanced methods to improve the accuracy and efficiency of these techniques. Initially, this report presents an extensive literature survey, looking at the few existing techniques for non-speech environmental sound recognition. This survey also, by necessity, investigates existing techniques used for sound recognition in speech and music. It also examines techniques used for direction detection of sounds. The techniques that have been identified are then comprehensively compared to determine the most appropriate techniques for non-speech sound recognition. A comprehensive comparison is performed using non-speech sounds and several runs are performed to ensure accuracy. These techniques are then ranked based on their effectiveness. The best technique is found to be either Continuous Wavelet Transform feature extraction with Dynamic Time Warping or Mel-Frequency Cepstral Coefficients with Dynamic Time Warping. Both of these techniques achieve a 70% recognition rate. Once the best of the existing classification techniques is identified, the problem of uncountable sounds in the environment can be addressed. Unlike speech recognition, non-speech sound recognition requires recognition from a much wider library of sounds. Due to this near-infinite set of example sounds, the characteristics and complexity of non-speech sound recognition techniques increases. To address this problem, a systematic scheme needs to be developed for non-speech sound classification. Several different approaches are examined. Included is a new design for an environmental sound taxonomy based on an environmental sound alphabet. This taxonomy works over three levels and classifies sounds based on their physical characteristics. Its performance is compared with a technique that generates a structured tree automatically. These structured techniques are compared for different data sets and results are analysed. Comparable results are achieved for these techniques with the same data set as previously used. In addition, the results and greater information from these experiments is used to infer some information about the structure of environmental sounds in general. Finally, conclusions are drawn on both sets of techniques and areas of future research stemming from this thesis are explored.
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Cowling, Michael. "Non-Speech Environmental Sound Classification System for Autonomous Surveillance." Thesis, Griffith University, 2004. http://hdl.handle.net/10072/365386.

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Sound is one of a human beings most important senses. After vision, it is the sense most used to gather information about the environment. Despite this, comparatively little research has been done into the field of sound recognition. The research that has been done mainly centres around the recognition of speech and music. Our auditory environment is made up of many sounds other than speech and music. This sound information can be taped into for the benefit of specific applications such as security systems. Currently, most researchers are ignoring this sound information. This thesis investigates techniques to recognise environmental non-speech sounds and their direction, with the purpose of using these techniques in an autonomous mobile surveillance robot. It also presents advanced methods to improve the accuracy and efficiency of these techniques. Initially, this report presents an extensive literature survey, looking at the few existing techniques for non-speech environmental sound recognition. This survey also, by necessity, investigates existing techniques used for sound recognition in speech and music. It also examines techniques used for direction detection of sounds. The techniques that have been identified are then comprehensively compared to determine the most appropriate techniques for non-speech sound recognition. A comprehensive comparison is performed using non-speech sounds and several runs are performed to ensure accuracy. These techniques are then ranked based on their effectiveness. The best technique is found to be either Continuous Wavelet Transform feature extraction with Dynamic Time Warping or Mel-Frequency Cepstral Coefficients with Dynamic Time Warping. Both of these techniques achieve a 70% recognition rate. Once the best of the existing classification techniques is identified, the problem of uncountable sounds in the environment can be addressed. Unlike speech recognition, non-speech sound recognition requires recognition from a much wider library of sounds. Due to this near-infinite set of example sounds, the characteristics and complexity of non-speech sound recognition techniques increases. To address this problem, a systematic scheme needs to be developed for non-speech sound classification. Several different approaches are examined. Included is a new design for an environmental sound taxonomy based on an environmental sound alphabet. This taxonomy works over three levels and classifies sounds based on their physical characteristics. Its performance is compared with a technique that generates a structured tree automatically. These structured techniques are compared for different data sets and results are analysed. Comparable results are achieved for these techniques with the same data set as previously used. In addition, the results and greater information from these experiments is used to infer some information about the structure of environmental sounds in general. Finally, conclusions are drawn on both sets of techniques and areas of future research stemming from this thesis are explored.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Information Technology
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Recoskie, Steven. "Autonomous Hybrid Powered Long Ranged Airship for Surveillance and Guidance." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31711.

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With devastating natural disasters on the rise, technological improvements are needed in the field of search and rescue (SAR). Unmanned aerial vehicles (UAVs) would be ideal for the search function such that manned vehicles can be prioritized to distributing first-aid and ultimately saving lives. One of the major reasons that UAVs are under utilized in SAR is that they lack a long flight endurance which compromises their effectiveness. Dirigibles are well suited for SAR missions since they can hover and maintain lift without consuming energy and can be easily deflated for packaging and transportation. This research focuses on extending flight endurance of small-scale airship UAVs through improvements to the infrastructure design and flight trajectory planning. In the first area, airship design methodologies are reviewed leading to the development and experimental testing two hybrid fuel-electric power plants. The prevailing hybrid power plant design consists of a 4-stroke 14cc gasoline engine in-line with a brushless DC motor/generator and variable pitch propeller. The results show that this design can produce enough mechanical and electrical power to support 72 hours of flight compared to 1-4 hours typical of purely electric designs. A power plant configuration comparison method was also developed to compare its performance and endurance to other power plant configurations that could be used in dirigible UAVs. Overall, the proposed hybrid power plant has a 600% increase in energy density over that of a purely electric configuration. In the second area, a comprehensive multi-objective cost function is developed using spatially variable wind vector fields generated from computational fluid dynamic analysis on digital elevations maps. The cost function is optimized for time, energy and collision avoidance using a wavefront expansion approach to produce feasible trajectories that obey the differential constraints of the airship platform. The simulated trajectories including 1) variable vehicle velocity, 2) variable wind vector field (WVF) data, and 3) high grid resolutions were found to consume 50% less energy on average compared to planned trajectories not considering one of these three characteristics. In its entirety, this research addresses current UAV flight endurance limitations and provides a novel UAV solution to SAR surveillance.
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Bernstein, Joshua I. (Joshua Ian) 1974. "System design for a rapid response autonomous aerial surveillance vehicle." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/50467.

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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1997.
Includes bibliographical references (p. 145-146).
The MIT/Draper Technology Development Partnership Project was conceived as a collaborative design and development program between MIT and Draper Laboratory. The overall aims of the two year project were to strengthen ties between the two institutions, to provide students with an opportunity to develop a first-of-a-kind system, and to foster a sense of entrepreneurship in the students working on the project. This first design team consisted of a mix of Master of Engineering and Master of Science students, along with undergraduate research assistants. The team began its work by reviewing the needs of the nation and the capabilities possessed by MIT and Draper which could be leveraged to address those needs. Candidate projects were then developed, and several were further refined through brief market assessments. Based on these assessments, a final project was chosen. The selected project, the Wide Area Surveillance Projectile (WASP), called for the development of a small, unmanned aerial vehicle which could be launched from an artillery gun to provide a rapid-response, time-critical reconnaissance capability for small military units or selected civilian applications. This thesis reviews the first year of work completed on the project. A systems view is used throughout, describing the top-level trades which were made to develop a product which would meet all of the user's needs. Specific attention is given to the interactions between the various subsystems and how these interactions contributed to the design solution developed by the team. In addition to this chronological description of the project, management lessons learned from the author's experience as project manager are presented, along with recommended approaches for future projects of a similar nature. These lessons may also find applications in the broader realm of rapid-prototyping engineering projects, as well as future projects undertaken as part of the MIT/Draper Technology Development Partnership Project.
by Joshua I. Bernstein.
M.Eng.
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Behara, Gayatri Mayukha. "Towards Autonomous Depth Perception for Surveillance in Real World Environments." University of Dayton / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1512398919937727.

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Nastasi, Kevin Michael. "Autonomous and Responsive Surveillance Network Management for Adaptive Space Situational Awareness." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/84931.

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As resident space object populations grow, and satellite propulsion capabilities improve, it will become increasingly challenging for space-reliant nations to maintain space situational awareness using current human-in-the-loop methods. This dissertation develops several real-time adaptive approaches to autonomous sensor network management for tracking multiple maneuvering and non-maneuvering satellites with a diversely populated Space Object Surveillance and Identification network. The proposed methods integrate suboptimal Partially Observed Markov Decision Processes (POMDPs) with covariance inflation or multiple model adaptive estimation techniques to task sensors and maintain viable orbit estimates for all targets. The POMDPs developed in this dissertation use information-based and system-based metrics to determine the rewards and costs associated with tasking a specific sensor to track a particular satellite. Like in real-world situations, the population of target satellites vastly outnumbers the available set of sensors. Robust and adaptable tasking algorithms are needed in this scenario to determine how and when sensors should be tasked. The strategies developed in this dissertation successfully track 207 non-maneuvering and maneuvering spacecraft using only 24 ground and space-based sensors. The results show that multiple model adaptive estimation coupled with a multi-metric, suboptimal POMDP can effectively and efficiently task a diverse network of sensors to track multiple maneuvering spacecraft, while simultaneously monitoring a large number of non-maneuvering objects. Overall, this dissertation demonstrates the potential for autonomous and adaptable sensor network command and control for real-world space situational awareness.
Ph. D.
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Herold, Fredrick W. "Total Border Security Surveillance." International Foundation for Telemetering, 2004. http://hdl.handle.net/10150/605061.

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International Telemetering Conference Proceedings / October 18-21, 2004 / Town & Country Resort, San Diego, California
This paper describes a system of Total Border Surveillance, which is cost effective, closes existing gaps and is less manpower intensive than the current techniques. The system utilizes a fleet of commercially available aircraft converted to unmanned capability, existing GPS and surveillance systems and autonomous ground stations to provide the desired coverage.
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Books on the topic "Autonomous surveillance"

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Savkin, Andrey V., Chao Huang, and Hailong Huang. Autonomous Navigation and Deployment of UAVs for Communication, Surveillance and Delivery. Wiley & Sons, Incorporated, John, 2022.

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Savkin, Andrey V., Chao Huang, and Hailong Huang. Autonomous Navigation and Deployment of UAVs for Communication, Surveillance and Delivery. Wiley & Sons, Incorporated, John, 2022.

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Autonomous Navigation and Deployment of UAVs for Communication, Surveillance and Delivery. Wiley & Sons, Limited, John, 2022.

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Savkin, Andrey V., Chao Huang, and Hailong Huang. Autonomous Navigation and Deployment of UAVs for Communication, Surveillance and Delivery. Wiley & Sons, Incorporated, John, 2022.

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Byler, Darren. Terror Capitalism. Duke University Press, 2021. http://dx.doi.org/10.1215/9781478022268.

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In Terror Capitalism anthropologist Darren Byler theorizes the contemporary Chinese colonization of the Uyghur Muslim minority group in the northwest autonomous region of Xinjiang. He shows that the mass detention of over one million Uyghurs in “reeducation camps” is part of processes of resource extraction in Uyghur lands that have led to what he calls terror capitalism—a configuration of ethnoracialization, surveillance, and mass detention that in this case promotes settler colonialism. Drawing on ethnographic fieldwork in the regional capital Ürümchi, Byler shows how media infrastructures, the state’s enforcement of “Chinese” cultural values, and the influx of Han Chinese settlers contribute to Uyghur dispossession and their expulsion from the city. He particularly attends to the experiences of young Uyghur men—who are the primary target of state violence—and how they develop masculinities and homosocial friendships to protect themselves against gendered, ethnoracial, and economic violence. By tracing the political and economic stakes of Uyghur colonization, Byler demonstrates that state-directed capitalist dispossession is coconstructed with a colonial relation of domination.
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Sincavage, Dr Suzanne, Dr Hans C. Mumm, Wayne Lonstein, CPT John Paul Hood, Randall Mai, Dr Mark Jackson, Mike Monnik, et al. DRONE DELIVERY OF CBNRECy – DEW WEAPONS Emerging Threats of Mini-Weapons of Mass Destruction and Disruption ( WMDD). Edited by Randall K. Nichols. New Prairie Press Open Book Publishing, 2022.

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Book chapters on the topic "Autonomous surveillance"

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Rai, Abhishek, Chirag Shah, and Nirav Shah. "Autonomous Water Surveillance Rover." In Advances in Intelligent Systems and Computing, 48–57. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16660-1_5.

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Ranasinghe, Nadeesha Oliver, and Wei-Min Shen. "Autonomous Surveillance Tolerant to Interference." In Advances in Autonomous Robotics, 73–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32527-4_7.

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Elmogy, Ahmed M., Alaa M. Khamis, and Fakhri Karray. "Market-Based Framework for Mobile Surveillance Systems." In Autonomous and Intelligent Systems, 69–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31368-4_9.

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Sriram, R., A. Vamsi, and S. Vigneshwari. "Telemetry-Based Autonomous Drone Surveillance System." In Advances in Systems, Control and Automations, 419–27. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8685-9_43.

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Martins-Filho, Luiz S., and Elbert E. N. Macau. "Trajectory Planning for Surveillance Missions of Mobile Robots." In Autonomous Robots and Agents, 109–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73424-6_13.

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Kowsalya, Ramaraj, and Parthasarathy Eswaran. "Development of Autonomous Quadcopter for Farmland Surveillance." In Soft Computing Systems, 80–87. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1936-5_9.

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Piciarelli, C., C. Micheloni, and G. L. Foresti. "An Autonomous Surveillance Vehicle for People Tracking." In Image Analysis and Processing – ICIAP 2005, 1140–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11553595_140.

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Katos, Vasilios, Frank Stowell, and Peter Bednar. "Surveillance, Privacy and the Law of Requisite Variety." In Data Privacy Management and Autonomous Spontaneous Security, 123–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19348-4_10.

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Orfanidis, Georgios, Savvas Apostolidis, Athanasios Kapoutsis, Konstantinos Ioannidis, Elias Kosmatopoulos, Stefanos Vrochidis, and Ioannis Kompatsiaris. "Autonomous Swarm of Heterogeneous Robots for Surveillance Operations." In Lecture Notes in Computer Science, 787–96. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34995-0_72.

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Bontzorlos, Tilemachos, Georgios Ch Sirakoulis, and Franciszek Seredynski. "Swarm Intelligence for Area Surveillance Using Autonomous Robots." In From Parallel to Emergent Computing, 315–44. Boca Raton, Florida : CRC Press, [2019] | Produced in celebration of the 25th anniversary of the International Journal of Parallel, Emergent, and Distributed Systems.: CRC Press, 2019. http://dx.doi.org/10.1201/9781315167084-15.

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Conference papers on the topic "Autonomous surveillance"

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Laou, P. "Autonomous surveillance microsystems." In Opto-Canada: SPIE Regional Meeting on Optoelectronics, Photonics, and Imaging, edited by John C. Armitage. SPIE, 2017. http://dx.doi.org/10.1117/12.2283944.

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de Vries, Jan S. "Autonomous wildfire surveillance." In SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, edited by Bjorn F. Andresen and Freeman D. Shepherd. SPIE, 1993. http://dx.doi.org/10.1117/12.160577.

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Flinchbaugh, Bruce E., and Thomas J. Olson. "Autonomous video surveillance." In 25th Annual AIPR Workshop on Emerging Applications of Computer Vision, edited by David H. Schaefer and Elmer F. Williams. SPIE, 1997. http://dx.doi.org/10.1117/12.267819.

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Kadhane, Rohit, Akshit Kumar, Kushal Bhattad, and Ashish Srivastava. "Surveillance Through Semi-Autonomous Bot." In 2021 International Conference on Design Innovations for 3Cs Compute Communicate Control (ICDI3C). IEEE, 2021. http://dx.doi.org/10.1109/icdi3c53598.2021.00038.

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Zingaretti, P., A. Mancini, E. Frontoni, A. Monteriu`, and S. Longhi. "Autonomous Helicopter for Surveillance and Security." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-35427.

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Abstract:
Unmanned Aerial Vehicles represent today an advanced and complex robotics platform for novel tasks. For example, UAVs can be used in applications for traffic monitoring and surveillance, emergency services assistance, photogrammetry and surveying. Generally, an UAV must be fully autonomous; autonomy is accomplished by a complex interconnection of systems related to a wide range of topics, e.g., flight low level control, navigation and task-based planning, elaboration of sensor signals, software architecture for reactive behaviours, communication. Today the challenge is the ability to insert UAVs in a cooperative network based on autonomous agents as UAV, UGV (Unmanned Ground Vehicle) to accomplish a specific task a priori defined. In this paper we introduce a prototype of autonomous aerial vehicle, the Helibot helicopter, specifically designed for applications as surveillance and security.
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Benaskeur, Abderrezak, Alaa Khamis, and Hengameh Irandoust. "Cooperation in distributed surveillance." In 2010 International Conference on Autonomous and Intelligent Systems (AIS). IEEE, 2010. http://dx.doi.org/10.1109/ais.2010.5547043.

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Kemp, M., A. L. Bertozzi, and D. Marthaler. "Multi-UUV perimeter surveillance." In 2004 IEEE/OES Autonomous Underwater Vehicles (IEEE Cat. No.04CH37578). IEEE, 2004. http://dx.doi.org/10.1109/auv.2004.1431200.

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Yu, Kuai, Fengjing Liu, Yunhe Liu, and Guo Li. "Autonomous Decision-making for Satellites Surveillance." In 2019 Chinese Control And Decision Conference (CCDC). IEEE, 2019. http://dx.doi.org/10.1109/ccdc.2019.8832717.

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de Vries, Jan S., and Rob A. W. Kemp. "Surveillance sensor for autonomous wildfire detection." In Optical Engineering and Photonics in Aerospace Sensing, edited by Sankaran Gowrinathan, C. Bruce Johnson, and James F. Shanley. SPIE, 1993. http://dx.doi.org/10.1117/12.161400.

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Markov, Vladimir, Anatoliy Khizhnyak, Joseph Chavez, Stephen Kupiec, Daniel A. Erwin, and Shiang Liu. "Autonomous intelligent modular surveillance system (AIM2S)." In SPIE Defense, Security, and Sensing, edited by William E. Thompson and Paul F. McManamon. SPIE, 2012. http://dx.doi.org/10.1117/12.919405.

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Reports on the topic "Autonomous surveillance"

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Abbot, Philip. Autonomous Wide Aperture Cluster For Surveillance. Fort Belvoir, VA: Defense Technical Information Center, September 2007. http://dx.doi.org/10.21236/ada573085.

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Joseph, John. Autonomous Wide Aperture Cluster for Surveillance (AWACS). Fort Belvoir, VA: Defense Technical Information Center, September 2008. http://dx.doi.org/10.21236/ada533981.

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Lynch, James F., and Glen Gawarkiewicz. Autonomous Wide Aperture Cluster for Surveillance (AWACS) - WHOI Component. Fort Belvoir, VA: Defense Technical Information Center, September 2008. http://dx.doi.org/10.21236/ada533819.

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Horowitz, Barry, Peter Beling, Kevin Skadron, Ron D. Williams, and William Melvin. Security Engineering Project - System Aware Cyber Security for an Autonomous Surveillance System On Board an Unmanned Aerial Vehicle. Fort Belvoir, VA: Defense Technical Information Center, January 2014. http://dx.doi.org/10.21236/ada608340.

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