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Journal articles on the topic 'Autonomous surveillance'

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Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

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1

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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2

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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3

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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4

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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6

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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7

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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8

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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9

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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10

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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11

Kemna, Stephanie, Michael J. Hamilton, David T. Hughes, and Kevin D. LePage. "Adaptive autonomous underwater vehicles for littoral surveillance." Intelligent Service Robotics 4, no. 4 (July 27, 2011): 245–58. http://dx.doi.org/10.1007/s11370-011-0097-4.

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12

Planthaber, Steffen, Daniel Kuehn, Kerstin Rohde, and Christian Hartberger. "Future control stations for heavy machinery." at - Automatisierungstechnik 70, no. 10 (October 1, 2022): 912–17. http://dx.doi.org/10.1515/auto-2022-0059.

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Abstract Robots and industrial vehicles are becoming more and more autonomous. Currently, the robots are not able to carry out all tasks autonomously, but the number of those tasks is increasing. Semi- autonomous robots are changing the requirements of control stations for their surveillance and control. These new technologies will provide the possibility to have a single operator command and supervise multiple (semi-) autonomous systems. This requires new control stations, which support remote control and also commanding autonomous actions, like executing a movement command to a specific position. Here, we provide a concept that combines classic and future control stations, that can already be used with the current state of the art in robotics.

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13

JANGRA, VISHAL, and SUNIL. "A Semi-Autonomos Drone for Surveillance and Security." INCAS BULLETIN 12, no. 4 (December 4, 2020): 267–70. http://dx.doi.org/10.13111/2066-8201.2020.12.4.25.

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A semi-autonomous aircraft to provide a real time surveillance in combat and rescue operation. It will fly autonomously ahead of user to find out the threats like distant enemies and traps like landmines. It will provide data about their position and things or ammunitions they have. It will use infrared and thermal imaging for night vision and powerful metal detection to find landmines and other traps. All data can be transmitted directly to the user on a helmet display or wrist screen. It will also provide warning about its findings. For positioning the threats it will provide GPS coordinates of threat. User can also operates it using the control unit.

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., Rajath Kumar M. P. "MASTER SLAVE AUTONOMOUS SURVEILLANCE BOT FOR MILITARY APPLICATIONS." International Journal of Research in Engineering and Technology 04, no. 07 (July 25, 2015): 477–82. http://dx.doi.org/10.15623/ijret.2015.0407077.

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15

Bontzorlos, Tilemachos, and Georgios Ch Sirakoulis. "Bioinspired algorithm for area surveillance using autonomous robots." International Journal of Parallel, Emergent and Distributed Systems 32, no. 4 (June 10, 2016): 368–85. http://dx.doi.org/10.1080/17445760.2016.1184269.

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16

Gekker, Alex, and Sam Hind. "Infrastructural surveillance." New Media & Society 22, no. 8 (October 10, 2019): 1414–36. http://dx.doi.org/10.1177/1461444819879426.

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This article proposes a new model of privacy: infrastructural surveillance. It departs from Agre’s classic distinction between surveillance and capture by examining the sociotechnical claims of connected and autonomous vehicles (CAVs) as requiring totalising surveillance of passengers and environment in order to operate. By doing so, it contributes to the ongoing debate on the commodification and platformisation of life, paying attention to the under-explored infrastructural requirements of certain digital technologies, rather than its business model. The article addresses four distinct characteristics of infrastructural surveillance: the aggregation of data, initialisation of protocols limiting possible actions, the prioritisation of distributed modes of governance and the enclosure of the driver in a personalised bubble of sovereign power. Ultimately, unlike previous modes of computer privacy in which activities are being constructed in real time from a set of institutionally standardised parts specified by a captured ontology, we observe the creation of new ontologies.

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17

Ubina, Naomi A., Shyi-Chyi Cheng, Hung-Yuan Chen, Chin-Chun Chang, and Hsun-Yu Lan. "A Visual Aquaculture System Using a Cloud-Based Autonomous Drones." Drones 5, no. 4 (October 2, 2021): 109. http://dx.doi.org/10.3390/drones5040109.

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This paper presents a low-cost and cloud-based autonomous drone system to survey and monitor aquaculture sites. We incorporated artificial intelligence (AI) services using computer vision and combined various deep learning recognition models to achieve scalability and added functionality, in order to perform aquaculture surveillance tasks. The recognition model is embedded in the aquaculture cloud, to analyze images and videos captured by the autonomous drone. The recognition models detect people, cages, and ship vessels at the aquaculture site. The inclusion of AI functions for face recognition, fish counting, fish length estimation and fish feeding intensity provides intelligent decision making. For the fish feeding intensity assessment, the large amount of data in the aquaculture cloud can be an input for analysis using the AI feeding system to optimize farmer production and income. The autonomous drone and aquaculture cloud services are cost-effective and an alternative to expensive surveillance systems and multiple fixed-camera installations. The aquaculture cloud enables the drone to execute its surveillance task more efficiently with an increased navigation time. The mobile drone navigation app is capable of sending surveillance alerts and reports to users. Our multifeatured surveillance system, with the integration of deep-learning models, yielded high-accuracy results.

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18

Wang, Chun Chieh, Ting En Lee, Kuo Hsien Hsia, Li Shan Ma, and Yi Chun Hsieh. "A Multi-Sensor Suspension Robot for Autonomous Detection and Surveillance." Applied Mechanics and Materials 190-191 (July 2012): 634–37. http://dx.doi.org/10.4028/www.scientific.net/amm.190-191.634.

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In this paper, a multi-sensor based suspension robot has been designed for the application of autonomous detection and surveillance. For fire fighters and rescuers, the disaster relief works are difficulty performed in the tunnels because of its constricted space. To reduce the losses of accident, the safety of tunnel should be ordinarily kept under surveillance. In the design of suspension robot, BASIC Stamp has been utilized as its control kernel and multiple sensors have been applied for detecting the emergencies. Once the surveillance center is announced of the emergencies, the fire fighters and rescuers could timely execute the saving mission.

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19

Gupta, Arpit. "Simulation and Detection of Small Drones/Suspicious UAVs in Drone Grid." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 5452–58. http://dx.doi.org/10.22214/ijraset.2021.36144.

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Today’s technology is evolving towards autonomous systems and the demand in autonomous drones, cars, robots, etc. has increased drastically in the past years. This project presents a solution for autonomous real-time visual detection and tracking of hostile drones by moving cameras equipped on surveillance drones. The algorithm developed in this project, based on state-of-art machine learning and computer vision methods, succeeds at autonomously detecting and tracking a single drone by moving a camera and can run at real-time. The project can be divided into two main parts: the detection and the tracking. The detection is based on the YOLOv3 (You Only Look Once v3) algorithm and a sliding window method. The tracking is based on the GOTURN (Generic Object Tracking Using Regression Networks) algorithm, which allows the tracking of generic objects at high speed. In order to allow autonomous tracking and enhance the accuracy, a combination of GOTURN and tracking by detection using YOLOv3 was developed.

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20

Jo, Daeil, and Yongjin Kwon. "Development of Autonomous VTOL UAV for Wide Area Surveillance." World Journal of Engineering and Technology 07, no. 01 (2019): 227–39. http://dx.doi.org/10.4236/wjet.2019.71015.

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21

Bharadwaj, Suda, Rayna Dimitrova, Jesse Quattrociocchi, and Ufuk Topcu. "Synthesis of strategies for autonomous surveillance on adversarial targets." Robotics and Autonomous Systems 153 (July 2022): 104084. http://dx.doi.org/10.1016/j.robot.2022.104084.

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22

VIKAS, KUMAR, KUMAR SAH ARUN, and KUMAR MOHANTY PRASES. "DESIGN AND IMPLEMENTATION OF AN AUTONOMOUS SURVEILLANCE MOBILE ROBOT." i-manager’s Journal on Future Engineering and Technology 14, no. 2 (2019): 42. http://dx.doi.org/10.26634/jfet.14.2.14856.

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23

Li, Jackson LiangYao, Alexander Zarbock, and Andrés Hidalgo. "Platelets as autonomous drones for hemostatic and immune surveillance." Journal of Experimental Medicine 214, no. 8 (July 18, 2017): 2193–204. http://dx.doi.org/10.1084/jem.20170879.

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Platelets participate in many important physiological processes, including hemostasis and immunity. However, despite their broad participation in these evolutionarily critical roles, the anucleate platelet is uniquely mammalian. In contrast with the large nucleated equivalents in lower vertebrates, we find that the design template for the evolutionary specialization of platelets shares remarkable similarities with human-engineered unmanned aerial vehicles in terms of overall autonomy, maneuverability, and expendability. Here, we review evidence illustrating how platelets are uniquely suited for surveillance and the manner in which they consequently provide various types of support to other cell types.

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24

Saptharishi, M., C. Spence Oliver, C. P. Diehl, K. S. Bhat, J. M. Dolan, A. Trebi-Ollennu, and P. K. Khosla. "Distributed surveillance and reconnaissance using multiple autonomous ATVs: CyberScout." IEEE Transactions on Robotics and Automation 18, no. 5 (October 2002): 826–36. http://dx.doi.org/10.1109/tra.2002.804501.

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25

Micheloni, Christian, Gian Luca Foresti, Claudio Piciarelli, and Luigi Cinque. "An Autonomous Vehicle for Video Surveillance of Indoor Environments." IEEE Transactions on Vehicular Technology 56, no. 2 (March 2007): 487–98. http://dx.doi.org/10.1109/tvt.2007.891478.

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26

Dupéré, Mélanie. "Surveillance and the Surrender of the Free Autonomous Self." Cultural Politics 13, no. 2 (July 1, 2017): 263–65. http://dx.doi.org/10.1215/17432197-4129281.

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27

Bontrager, Nick, and Adam Fung. "Autonomous Art Systems: an introduction." Media-N 15, no. 1 (January 21, 2019): 1–2. http://dx.doi.org/10.21900/j.median.v15i1.73.

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Media-N, the Journal of the New Media Caucus, invited submissions for this issue about the use of Autonomous Art Systems, tethered and untethered systems of making, autonomous vehicles, and related programming in creative fields of study. Relevant subjects included: artworks that address concepts of drones or surveillance as subject or form; the influence of emerging technologies on studio art practices; or critical/historical analysis of the entanglement of art and technology.

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28

Cho, Kuk, and Dooyong Cho. "Autonomous Driving Assistance with Dynamic Objects Using Traffic Surveillance Cameras." Applied Sciences 12, no. 12 (June 20, 2022): 6247. http://dx.doi.org/10.3390/app12126247.

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This paper describes a method that precisely estimates the position of images of traffic surveillance camera objects. We suggest a projection method with multiple traffic surveillance cameras through a local coordinate system into a global coordinate system. The transformation of coordinates uses detected objects, parameters of the camera and the geometric information of high- definition (HD) maps. Traffic surveillance cameras that pursue traffic safety and convenience use various sensors to generate traffic information. We suggest a transformation method with images of the camera and HD maps and an evaluation method. Therefore, it is necessary to improve the sensor-related technology to increase the efficiency and reliability of the traffic information. Recently, the role of the camera in collecting video information has become more important due to advances in artificial intelligence (AI) technology. The objects projected from the traffic surveillance camera domain to the HD domain are helpful to identify imperceptible zones, such as blind spots, on roads for autonomous driving assistance. In this study, we proposed to identify and track dynamic objects (vehicles, pedestrian, etc.) with traffic surveillance cameras, and to analyze and provide information about them in various environments. To this end, we conducted the identification of dynamic objects using the Yolov4 and DeepSort algorithms, established real-time multi-user support servers based on Kafka, defined transformation matrices between images and spatial coordinate systems, and implemented map-based dynamic object visualization. In addition, a positional consistency evaluation was performed to confirm its usefulness. Through the proposed scheme, we confirmed that multiple traffic surveillance cameras can serve as important sensors to provide relevant information by analyzing road conditions in real-time in terms of road infrastructure beyond a simple monitoring role.

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29

Bernardini, Sara, Maria Fox, and Derek Long. "Planning the Behaviour of Low-Cost Quadcopters for Surveillance Missions." Proceedings of the International Conference on Automated Planning and Scheduling 24 (May 11, 2014): 445–53. http://dx.doi.org/10.1609/icaps.v24i1.13670.

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Micro Aerial Vehicles (MAVs) are increasingly regarded as a valid low-cost alternative to UAVs and ground robots in surveillance missions and a number of other civil and military applications. Research on autonomous MAVs is still in its infancy and has focused almost exclusively on integrating control and computer vision techniques to achieve reliable autonomous flight. In this paper, we describe our approach to using automated planning in order to elicit high-level intelligent behaviour from autonomous MAVs engaged in surveillance applications. Planning offers effective tools to handle the unique challenges faced by MAVs that relate to their fast and unstable dynamics as well as their low endurance and small payload capabilities. We demonstrate our approach by focusing on the "Parrot AR.Drone2.0" quadcopter and Search-and-Tracking missions, which involve searching for a mobile target and tracking it after it is found.

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30

Al-Kaff, Abdulla, Ángel Madridano, Sergio Campos, Fernando García, David Martín, and Arturo de la Escalera. "Emergency Support Unmanned Aerial Vehicle for Forest Fire Surveillance." Electronics 9, no. 2 (February 4, 2020): 260. http://dx.doi.org/10.3390/electronics9020260.

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The advances in autonomous technologies and microelectronics have increased the use of Autonomous Unmanned Aerial Vehicles (UAVs) in more critical applications, such as forest fire monitoring and fighting. In addition, implementing surveillance methods that provide rich information about the fires is considered a great tool for Emergency Response Teams (ERT). From this aspect and in collaboration with Telefónica Digital España, Dronitec S.L, and Divisek Systems, this paper presents a fire monitoring system based on perception algorithms, implemented on a UAV, to perform surveillance tasks allowing the monitoring of a specific area, in which several algorithms have been implemented to perform the tasks of autonomous take-off/landing, trajectory planning, and fire monitoring. This UAV is equipped with RGB and thermal cameras, temperature sensors, and communication modules in order to provide full information about the fire and the UAV itself, sending these data to the ground station in real time. The presented work is validated by performing several flights in a real environment, and the obtained results show the efficiency and the robustness of the proposed system, against different weather conditions.

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31

Ramli, Hanif, Wahyu Kuntjoro, and Ahmad Khushairy Makhtar. "Advanced Autonomous Multirotor Response System." Applied Mechanics and Materials 393 (September 2013): 299–304. http://dx.doi.org/10.4028/www.scientific.net/amm.393.299.

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Autonomous Unmanned Aerial Vehicle (UAV) in the form of multi-rotor system is having a great potential in various applications such as disaster management (as first response system) and surveillance. It is known that conventional helicopter system, capable of hovering, is practical and reliable as many applications have confirmed its capabilities. However it is only achievable once highly optimized control architecture is realized. The objective of the research presented in this paper is, to develop a small multi rotor UAV system that is able to autonomously flying from one way point to another in a stable manner. This small UAV is termed as Mini (or Micro) Aerial Vehicle (MAV). In this project, a four-rotor system was developed, and becoming the platform of various sensors system, flight control system, and electric propulsion system. The MAV was programmed to be able to lift off and fly to waypoints making use of GPS. This paper presents the architecture of the MAV and its autonomous flight.

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32

Navarro Roa, Jonnathan, Félix Parca Acevedo, and Giovani Mancilla Gaona. "Radar and UAV: georeferencing and airspace surveillance system." Visión electrónica 11, no. 2 (October 27, 2018): 190–99. http://dx.doi.org/10.14483/22484728.14627.

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A ¨RADAR¨ system, from the English Acronym ¨Radio Detention and Ranging¨. Better known as ¨Radio Detection and Location¨ RDL. It is a system for detecting and positioning objects through shipping and reflection of electromagnetic waves in terms of the time of issue and the return of the waves and their speed (calculated by the Doppler effect of the electromagnetic signal received). Meanwhile, an autonomous unmanned vehicle, also known as Unmanned Aerial Vehicle, UAV, which is defined as an aircraft which does not carry a human operator, and uses aerodynamic forces to provide airlift by itself. Therefore, it can fly autonomously or it can be operated by remote control. This article focuses on the review of experiences where these two technologies are integrated, particularly UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar). This is done in order to support research concerning the combination thereof to be applied in georeferencing humanitarian missions or military missions that require monitoring of airspace.

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Meguro, Jun-ichi, Rui Hirokawa, Jun-ichi Takiguchi, and Takumi Hashizume. "Autonomous Mobile Surveillance Based on RTK-GPS in Urban Canyons." Journal of Robotics and Mechatronics 17, no. 2 (April 20, 2005): 218–25. http://dx.doi.org/10.20965/jrm.2005.p0218.

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This paper describes an autonomous mobile surveillance used in plants in high-rise buildings. This consists of a wireless LAN, a base station, and an autonomous vehicle. The vehicle uses GPS/INS navigation using network-based Real-Time Kinematic GPS (RTK-GPS) with Positioning Augmentation Services (PASTM, Mitsubishi Electric Corporation 2003), an Area Laser Radar (ALR), a slave camera, and an Omni-Directional Vision (ODV) sensor for surveillance and reconnaissance. The vehicle switches control modes – normal, road tracking, and crossing recognition – based on vehicle navigation error. A field test shows that the vehicle tracks a planned straight paths within 0.10m accuracy and planned curved paths within 0.25m even without RTK fixed solutions. Field experiments and analysis prove that the proposed navigation provides sufficient navigation and guidance accuracy under poor satellite geometry and visibility, and that the panorama image database with absolute positioning is useful for surveillance.

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Ejofodomi, O'tega, and Godswill Ofualagba. "Subsea Crude Oil Spill Detection Using Robotic Systems." European Journal of Engineering Research and Science 4, no. 12 (December 27, 2019): 112–16. http://dx.doi.org/10.24018/ejers.2019.4.12.1684.

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Underwater Robotic Oil Spill Surveillance (UROSS) system provides constant and autonomous spill surveillance for subsea pipelines. M900 embedded Radio Frequency Identification tags and readers are used to identify pipeline section for surveillance. GY-521 gyrometer and XL-MaxSonar-WR1 ultrasound sensor are used for autonomous navigation. Spills are detected using a METS methane sensor. After spill detection, images of spill site are captured with a L3C-400 Micro Ultras-Miniature Color Camera and spill location is obtained using GPS. Spill Images and location are transmitted to a remote PC on the nearest off shore platform using an Xbee Pro 900HP wireless connection. An Ocean Signal rescueME Personal Beacon Locator transmits a 406 MHz distress signal via satellite to emergency services communicating the identification of a spill. Power analysis showed the system’s ability to remain submerged and to provide surveillance for 100 m sections of a subsea pipeline once every 24 hrs for a month, and can be increased to every hour for 51 months.

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35

Ejofodomi, O'tega, and Godswill Ofualagba. "Subsea Crude Oil Spill Detection Using Robotic Systems." European Journal of Engineering and Technology Research 4, no. 12 (December 27, 2019): 112–16. http://dx.doi.org/10.24018/ejeng.2019.4.12.1684.

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Underwater Robotic Oil Spill Surveillance (UROSS) system provides constant and autonomous spill surveillance for subsea pipelines. M900 embedded Radio Frequency Identification tags and readers are used to identify pipeline section for surveillance. GY-521 gyrometer and XL-MaxSonar-WR1 ultrasound sensor are used for autonomous navigation. Spills are detected using a METS methane sensor. After spill detection, images of spill site are captured with a L3C-400 Micro Ultras-Miniature Color Camera and spill location is obtained using GPS. Spill Images and location are transmitted to a remote PC on the nearest off shore platform using an Xbee Pro 900HP wireless connection. An Ocean Signal rescueME Personal Beacon Locator transmits a 406 MHz distress signal via satellite to emergency services communicating the identification of a spill. Power analysis showed the system’s ability to remain submerged and to provide surveillance for 100 m sections of a subsea pipeline once every 24 hrs for a month, and can be increased to every hour for 51 months.

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36

Di Paola, Donato, Annalisa Milella, Grazia Cicirelli, and Arcangelo Distante. "An Autonomous Mobile Robotic System for Surveillance of Indoor Environments." International Journal of Advanced Robotic Systems 7, no. 1 (March 2010): 8. http://dx.doi.org/10.5772/7254.

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37

Gorkin, Robert, Kye Adams, Matthew J. Berryman, Sam Aubin, Wanqing Li, Andrew R. Davis, and Johan Barthelemy. "Sharkeye: Real-Time Autonomous Personal Shark Alerting via Aerial Surveillance." Drones 4, no. 2 (May 4, 2020): 18. http://dx.doi.org/10.3390/drones4020018.

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While aerial shark spotting has been a standard practice for beach safety for decades, new technologies offer enhanced opportunities, ranging from drones/unmanned aerial vehicles (UAVs) that provide new viewing capabilities, to new apps that provide beachgoers with up-to-date risk analysis before entering the water. This report describes the Sharkeye platform, a first-of-its-kind project to demonstrate personal shark alerting for beachgoers in the water and on land, leveraging innovative UAV image collection, cloud-hosted machine learning detection algorithms, and reporting via smart wearables. To execute, our team developed a novel detection algorithm trained via machine learning based on aerial footage of real sharks and rays collected at local beaches, hosted and deployed the algorithm in the cloud, and integrated push alerts to beachgoers in the water via a shark app to run on smartwatches. The project was successfully trialed in the field in Kiama, Australia, with over 350 detection events recorded, followed by the alerting of multiple smartwatches simultaneously both on land and in the water, and with analysis capable of detecting shark analogues, rays, and surfers in average beach conditions, and all based on ~1 h of training data in total. Additional demonstrations showed potential of the system to enable lifeguard-swimmer communication, and the ability to create a network on demand to enable the platform. Our system was developed to provide swimmers and surfers with immediate information via smart apps, empowering lifeguards/lifesavers and beachgoers to prevent unwanted encounters with wildlife before it happens.

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Julian, Kyle D., and Mykel J. Kochenderfer. "Distributed Wildfire Surveillance with Autonomous Aircraft Using Deep Reinforcement Learning." Journal of Guidance, Control, and Dynamics 42, no. 8 (August 2019): 1768–78. http://dx.doi.org/10.2514/1.g004106.

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Bernardini, Sara, Maria Fox, and Derek Long. "Combining temporal planning with probabilistic reasoning for autonomous surveillance missions." Autonomous Robots 41, no. 1 (December 28, 2015): 181–203. http://dx.doi.org/10.1007/s10514-015-9534-0.

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Chandrakala, S., and S. L. Jayalakshmi. "Environmental Audio Scene and Sound Event Recognition for Autonomous Surveillance." ACM Computing Surveys 52, no. 3 (July 27, 2019): 1–34. http://dx.doi.org/10.1145/3322240.

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Zhang, Chao, Quanzhong Zhan, Qi Wang, Haichao Wu, Ting He, and Yi An. "Autonomous Dam Surveillance Robot System Based on Multi-Sensor Fusion." Sensors 20, no. 4 (February 17, 2020): 1097. http://dx.doi.org/10.3390/s20041097.

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Dams are important engineering facilities in the water conservancy industry. They have many functions, such as flood control, electric power generation, irrigation, water supply, shipping, etc. Therefore, their long-term safety is crucial to operational stability. Because of the complexity of the dam environment, robots with various kinds of sensors are a good choice to replace humans to perform a surveillance job. In this paper, an autonomous system design is proposed for dam ground surveillance robots, which includes general solution, electromechanical layout, sensors scheme, and navigation method. A strong and agile skid-steered mobile robot body platform is designed and created, which can be controlled accurately based on an MCU and an onboard IMU. A novel low-cost LiDAR is adopted for odometry estimation. To realize more robust localization results, two Kalman filter loops are used with the robot kinematic model to fuse wheel encoder, IMU, LiDAR odometry, and a low-cost GNSS receiver data. Besides, a recognition network based on YOLO v3 is deployed to realize real-time recognition of cracks and people during surveillance. As a system, by connecting the robot, the cloud server and the users with IOT technology, the proposed solution could be more robust and practical.

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G V, Abhishek. "Autonomous Intelligent POD for Military Purpose." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 14, 2021): 839–48. http://dx.doi.org/10.22214/ijraset.2021.35068.

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At present, the surveillance of International border areas is a challenging task. The border guarding forces are patrolling the border seriously, but it is no longer viable to watch the border at each and every moment. A critical requirement of this state of affairs is a robot that robotically detects trespasser in the border and reports close by board security control unit. Many of the army departments now make use of robots to elevate out risky jobs that can't be executed by means of the soldiers. In this present work, a Raspbian working system-based undercover agent robot platform with far off monitoring and manage algorithm through the Internet of Things (IoT)has been developed which will save human lives, reduces manual error and protect us from enemies. The spy robotic device comprises the Raspberry Pi (small single-board computer), pi camera and sensors. The information regarding the detection of living objects with the aid of the PIR sensor is dispatched to the users thru the net server and pi digicam capture the moving object which is posted inner the webpage simultaneously. The consumer in the manipulate room in a position to access the robot with wheel drive control buttons on the webpage. The movement of a robotic is also controlled robotically via obstacle detecting sensors to avoiding collisions. This surveillance system using a spy robot can be custom-made for more than a few fields like industries, banks and shopping malls.

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Hutchinson, William. "Deceiving Autonomous Drones." International Journal of Cyber Warfare and Terrorism 10, no. 3 (July 2020): 1–14. http://dx.doi.org/10.4018/ijcwt.2020070101.

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This speculative article examines the concept of deceiving autonomous drones that are controlled by artificial intelligence (AI) and can work without operational input from humans. This article examines the potential of autonomous drones, their implications and how deception could possibly be a defence against them and /or a means of gaining advantage. It posits that officially, no truly autonomous drone is operational now, yet the development of AI and other technologies could expand the capabilities of these devices, which will inevitably confront society with a number of deep ethical, legal, and philosophical issues. The article also examines the impact of autonomous drones and their targets in terms of the power/deception nexus. The impact of surveillance and kinetic impacts on the target populations is investigated. The use of swarms can make deception more difficult although security can be breached. The Internet of Things can be considered as based on the same model as a swarm and its impact on human behaviour indicates that deception or perhaps counter-deception should be considered as a defence. Finally, the issues raised are outlined. However, this article does not provide definitive answers but, hopefully, exposes a number of issues that will stimulate further discussion and research in this general area.

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Ruscetti, Marcus, Josef Leibold, Matthew J. Bott, Myles Fennell, Amanda Kulick, Nelson R. Salgado, Chi-Chao Chen, et al. "NK cell–mediated cytotoxicity contributes to tumor control by a cytostatic drug combination." Science 362, no. 6421 (December 20, 2018): 1416–22. http://dx.doi.org/10.1126/science.aas9090.

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Molecularly targeted therapies aim to obstruct cell autonomous programs required for tumor growth. We show that mitogen-activated protein kinase (MAPK) and cyclin-dependent kinase 4/6 inhibitors act in combination to suppress the proliferation of KRAS-mutant lung cancer cells while simultaneously provoking a natural killer (NK) cell surveillance program leading to tumor cell death. The drug combination, but neither agent alone, promotes retinoblastoma (RB) protein-mediated cellular senescence and activation of the immunomodulatory senescence-associated secretory phenotype (SASP). SASP components tumor necrosis factor–α and intercellular adhesion molecule–1 are required for NK cell surveillance of drug-treated tumor cells, which contributes to tumor regressions and prolonged survival in a KRAS-mutant lung cancer mouse model. Therefore, molecularly targeted agents capable of inducing senescence can produce tumor control through non–cell autonomous mechanisms involving NK cell surveillance.

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Soroosh, Mahmoodi, Shapola Malala Stembinkosi, and Hamedia Parisa. "An Experimental Study on Surveillance Robot Using Raspberry Pi." Annals of Robotics and Automation 6, no. 1 (September 28, 2022): 001–6. http://dx.doi.org/10.17352/ara.000015.

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Recently, robots have been developed to reduce human resources and observation time in a fast, booming, and rapidly growing technology. In this study, a surveillance robot is designed and manufactured to move around a given surrounding, preferably a domestic environment, record video & audio and send the information to the user through a network. The robot is allowed to be controlled wirelessly using Raspberry Pi technology from a location remotely using IoT technology. This sensor-based robot uses the Raspberry Pi with Ethernet, WI-Fi and Bluetooth for networking purposes. Python is chosen as the programming language in both autonomous and semi-autonomous modes. The manufactured robot was experimentally tested. The recorded videos, images and audio are successfully transferred through a WiFi network to the end user. The user could also control and move the robot in different directions for specific demands. The designed simple robot interests users to record and transfer information for the safety of their indoors.

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Mihailescu, Cristina, and Ioan Farcasan. "Mathematical Model for Studying the Evolution of Multi-Role Unmanned Aerial Vehicle in Turbulent Atmosphere." Applied Mechanics and Materials 325-326 (June 2013): 984–89. http://dx.doi.org/10.4028/www.scientific.net/amm.325-326.984.

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The paper purpose is to present some aspects regarding the control system of unmanned aerial vehicle - UAV, used for local observations, surveillance and monitoring of interest area or as a training target for anti-aircraft systems. The calculus methodology allows a numerical simulation of UAV evolution in bad atmospheric conditions by using a nonlinear model, as well as a linear one for obtaining the guidance command. The UAV model which will be presented has six DOF (degrees of freedom), and an autonomous control system. This theoretical development allows us to build the stability matrix, command matrix and the control matrix and finally to analyze the stability of autonomous UAV flight. A robust guidance system, based on Kalman filter will be evaluated for different fly conditions and the results will be presented. The flight parameters and guidance will be analyzed. The paper is inspired by national project SAMO (Autonomous Aerial Monitoring System for Interest Areas of Great Endurance). Keywords: UAV, Simulation, Control, Guidance, Endurance, Surveillance, Monitoring, Kalman filter

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Alvarez Leon, Luis F. "Eyes on the Road: Surveillance Logics in the Autonomous Vehicle Economy." Surveillance & Society 17, no. 1/2 (March 31, 2019): 198–204. http://dx.doi.org/10.24908/ss.v17i1/2.12932.

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As emblematic products of a previous industrial era, cars are often tied to a sphere outside the digital economy and its ruling logics and are, therefore, governed by different ideas of privacy, agency, and sovereignty. However, as self-driving cars gain momentum, computerization, and automation, their platformization contributes to transforming the automobile as technology, industry, and cultural artifact. This creates new spaces of consumption within cars, around them, and between them—all of which are premised on highly detailed contextual information that is collected, processed, and transmitted in the process of navigation. Thus, the ads and entertainment delivered to passengers, the landscapes surrounding the vehicles, and the proprietary data networks that link self-driving car fleets are all redefined as revenue streams in the new auto economy. This paper explores the transformation of the existing auto economy in the context of the emergence of self-driving cars by following the transposition of surveillance logics that are central to the digital economy and by considering the implications of their adaptation to the arena of automated mobility.

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Zaaba, ZarulFitri. "Improvement of Availability of Level Crossing System by Autonomous Surveillance Camera." International Innovative Research Journal of Engineering and Technology 3, no. 4 (June 30, 2018): 4–5. http://dx.doi.org/10.32595/iirjet.org/v3i4.2018.68.

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Chandrakantha Sharma B V et al.,, Chandrakantha Sharma B. V. et al ,. "Design and Fabrication of Autonomous Aircraft Delivery, Monitoring and Surveillance System." International Journal of Mechanical and Production Engineering Research and Development 10, no. 3 (2020): 8931–42. http://dx.doi.org/10.24247/ijmperdjun2020850.

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Garate, B., S. Díaz, S. Iturriaga, S. Nesmachnow, V. Shepelev, and A. Tchernykh. "Autonomous Swarm of Low-Cost Commercial Unmanned Aerial Vehicles for Surveillance." Programming and Computer Software 47, no. 8 (December 2021): 558–77. http://dx.doi.org/10.1134/s0361768821080120.

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