Academic literature on the topic 'Sensors on dynamic environments'

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Journal articles on the topic "Sensors on dynamic environments"

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Müller, Simone, and Dieter Kranzlmüller. "Dynamic Sensor Matching based on Geomagnetic Inertial Navigation." Journal of WSCG 30, no. 1-2 (2022): 16–25. http://dx.doi.org/10.24132/jwscg.2022.3.

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Optical sensors can capture dynamic environments and derive depth information in near real-time. The quality of these digital reconstructions is determined by factors like illumination, surface and texture conditions, sensing speed and other sensor characteristics as well as the sensor-object relations. Improvements can be obtained by us- ing dynamically collected data from multiple sensors. However, matching the data from multiple sensors requires a shared world coordinate system. We present a concept for transferring multi-sensor data into a commonly ref- erenced world coordinate system: the earth’s magnetic field. The steady presence of our planetary magnetic field provides a reliable world coordinate system, which can serve as a reference for a position-defined reconstruction of dynamic environments. Our approach is evaluated using magnetic field sensors of the ZED 2 stereo camera from Stereolabs, which provides orientation relative to the North Pole similar to a compass. With the help of inertial measurement unit informations, each camera’s position data can be transferred into the unified world coordinate system. Our evaluation reveals the level of quality possible using the earth magnetic field and allows a basis for dynamic and real-time-based applications of optical multi-sensors for environment detection.
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Gao, Rui, Wenjun Zhang, Junmin Jing, et al. "Design, Fabrication, and Dynamic Environmental Test of a Piezoresistive Pressure Sensor." Micromachines 13, no. 7 (2022): 1142. http://dx.doi.org/10.3390/mi13071142.

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Microelectromechanical system (MEMS) pressure sensors have a wide range of applications based on the advantages of mature technology and easy integration. Among them, piezoresistive sensors have attracted great attention with the advantage of simple back-end processing circuits. However, less research has been reported on the performance of piezoresistive pressure sensors in dynamic environments, especially considering the vibrations and shocks frequently encountered during the application of the sensors. To address these issues, this paper proposes a design method for a MEMS piezoresistive pressure sensor, and the fabricated sensor is evaluated in a series of systematic dynamic environmental adaptability tests. After testing, the output sensitivity of the sensor chip was 9.21 mV∙bar−1, while the nonlinearity was 0.069% FSS. The sensor overreacts to rapidly changing pressure environments and can withstand acceleration shocks of up to 20× g. In addition, the sensor is capable of providing normal output over the vibration frequency range of 0–5000 Hz with a temperature coefficient sensitivity of −0.30% FSS °C−1 over the temperature range of 0–80 °C. Our proposed sensor can play a key role in applications with wide pressure ranges, high-frequency vibrations, and high acceleration shocks, as well as guide MEMS-based pressure sensors in high pressure ranges and complex environmental adaptability in their design.
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Fox, D., W. Burgard, and S. Thrun. "Markov Localization for Mobile Robots in Dynamic Environments." Journal of Artificial Intelligence Research 11 (November 23, 1999): 391–427. http://dx.doi.org/10.1613/jair.616.

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Localization, that is the estimation of a robot's location from sensor data, is a fundamental problem in mobile robotics. This papers presents a version of Markov localization which provides accurate position estimates and which is tailored towards dynamic environments. The key idea of Markov localization is to maintain a probability density over the space of all locations of a robot in its environment. Our approach represents this space metrically, using a fine-grained grid to approximate densities. It is able to globally localize the robot from scratch and to recover from localization failures. It is robust to approximate models of the environment (such as occupancy grid maps) and noisy sensors (such as ultrasound sensors). Our approach also includes a filtering technique which allows a mobile robot to reliably estimate its position even in densely populated environments in which crowds of people block the robot's sensors for extended periods of time. The method described here has been implemented and tested in several real-world applications of mobile robots, including the deployments of two mobile robots as interactive museum tour-guides.
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Russell, Joseph, Jeroen H. M. Bergmann, and Vikranth H. Nagaraja. "Towards Dynamic Multi-Modal Intent Sensing Using Probabilistic Sensor Networks." Sensors 22, no. 7 (2022): 2603. http://dx.doi.org/10.3390/s22072603.

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Intent sensing—the ability to sense what a user wants to happen—has many potential technological applications. Assistive medical devices, such as prosthetic limbs, could benefit from intent-based control systems, allowing for faster and more intuitive control. The accuracy of intent sensing could be improved by using multiple sensors sensing multiple environments. As users will typically pass through different sensing environments throughout the day, the system should be dynamic, with sensors dropping in and out as required. An intent-sensing algorithm that allows for this cannot rely on training from only a particular combination of sensors. It should allow any (dynamic) combination of sensors to be used. Therefore, the objective of this study is to develop and test a dynamic intent-sensing system under changing conditions. A method has been proposed that treats each sensor individually and combines them using Bayesian sensor fusion. This approach was tested on laboratory data obtained from subjects wearing Inertial Measurement Units and surface electromyography electrodes. The proposed algorithm was then used to classify functional reach activities and compare the performance to an established classifier (k-nearest-neighbours) in cases of simulated sensor dropouts. Results showed that the Bayesian sensor fusion algorithm was less affected as more sensors dropped out, supporting this intent-sensing approach as viable in dynamic real-world scenarios.
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Zainab, Begum, Tahreem Fatima Nisaa, Suzana, Harish Joshi Dr, Kausar Prof.Uzma, and Bawge Prof.Ashok. "Smart Sensors: A Comprehensive Survey of IoT Sensor Types and Applications." Journal of Emerging Trends in Electrical Engineering 7, no. 2 (2025): 16–24. https://doi.org/10.5281/zenodo.15573961.

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<em>The Internet of Things (IoT) is a transformative technology, redefining modern life by embedding billions of sensors and actuators into everyday environments. This integration yields intelligent, connected scenarios where continuous data capture provides a comprehensive operational view. Widely recognized in academic research, sensors facilitate ubiquitous data acquisition and are pivotal for diverse IoT applications. This paper explores a wide range of IoT sensors and examines various sensor-driven applications that help form smart environments. By evaluating multiple sensor application areas, we identify optimal sensor configurations for distinct IoT scenarios, thereby laying a robust foundation for future advancements in this dynamic domain.</em>
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Yoon, John. "Trustworthiness of Dynamic Moving Sensors for Secure Mobile Edge Computing." Computers 7, no. 4 (2018): 63. http://dx.doi.org/10.3390/computers7040063.

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Wireless sensor network is an emerging technology, and the collaboration of wireless sensors becomes one of the active research areas for utilizing sensor data. Various sensors collaborate to recognize the changes of a target environment, to identify, if any radical change occurs. For the accuracy improvement, the calibration of sensors has been discussed, and sensor data analytics are becoming popular in research and development. However, they are not satisfactorily efficient for the situations where sensor devices are dynamically moving, abruptly appearing, or disappearing. If the abrupt appearance of sensors is a zero-day attack, and the disappearance of sensors is an ill-functioning comrade, then sensor data analytics of untrusted sensors will result in an indecisive artifact. The predefined sensor requirements or meta-data-based sensor verification is not adaptive to identify dynamically moving sensors. This paper describes a deep-learning approach to verify the trustworthiness of sensors by considering the sensor data only. The proposed verification on sensors can be done without having to use meta-data about sensors or to request consultation from a cloud server. The contribution of this paper includes (1) quality preservation of sensor data for mining analytics. The sensor data are trained to identify their characteristics of outliers: whether they are attack outliers, or outlier-like abrupt changes in environments; and (2) authenticity verification of dynamically moving sensors, which was possible. Previous unknown sensors are also identified by deep-learning approach.
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Schulte-Tigges, Joschua, Marco Förster, Gjorgji Nikolovski, et al. "Benchmarking of Various LiDAR Sensors for Use in Self-Driving Vehicles in Real-World Environments." Sensors 22, no. 19 (2022): 7146. http://dx.doi.org/10.3390/s22197146.

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In this paper, we report on our benchmark results of the LiDAR sensors Livox Horizon, Robosense M1, Blickfeld Cube, Blickfeld Cube Range, Velodyne Velarray H800, and Innoviz Pro. The idea was to test the sensors in different typical scenarios that were defined with real-world use cases in mind, in order to find a sensor that meet the requirements of self-driving vehicles. For this, we defined static and dynamic benchmark scenarios. In the static scenarios, both LiDAR and the detection target do not move during the measurement. In dynamic scenarios, the LiDAR sensor was mounted on the vehicle which was driving toward the detection target. We tested all mentioned LiDAR sensors in both scenarios, show the results regarding the detection accuracy of the targets, and discuss their usefulness for deployment in self-driving cars.
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Wang, Y., D. Ewert, T. Meisen, D. Schilberg, and S. Jeschke. "Work area monitoring in dynamic environments using multiple auto-aligning 3-D sensors." Journal of Sensors and Sensor Systems 3, no. 1 (2014): 113–20. http://dx.doi.org/10.5194/jsss-3-113-2014.

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Abstract. Compared to current industry standards future production systems will be more flexible and robust and will adapt to unforeseen states and events. Industrial robots will interact with each other as well as with human coworkers. To be able to act in such a dynamic environment, each acting entity ideally needs complete knowledge of its surroundings, concerning working materials as well as other working entities. Therefore new monitoring methods providing complete coverage for complex and changing working areas are needed. While single 3-D sensors already provide detailed information within their field of view, complete coverage of a complete work area can only be achieved by relying on a multitude of these sensors. However, to provide useful information all data of each sensor must be aligned to each other and fused into an overall world picture. To be able to align the data correctly, the position and orientation of each sensor must be known with sufficient exactness. In a quickly changing dynamic environment, the positions of sensors are not fixed, but must be adjusted to maintain optimal coverage. Therefore, the sensors need to autonomously align themselves in real time. This can be achieved by adding defined markers with given geometrical patterns to the environment which can be used for calibration and localization of each sensor. As soon as two sensors detect the same markers, their relative position to each other can be calculated. Additional anchor markers at fixed positions serve as global reference points for the base coordinate system. In this paper we present a prototype for a self-aligning monitoring system based on a robot operating system (ROS) and Microsoft Kinect. This system is capable of autonomous real-time calibration relative to and with respect to a global coordinate system as well as to detect and track defined objects within the working area.
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Liu, Ning Han, Hsiang Ming Hsu, and Tien Cheng Huang. "Enhanced Approaches for Processing Window Queries in Dynamic Wireless Sensor Networks." Applied Mechanics and Materials 58-60 (June 2011): 2122–27. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.2122.

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Due to the proliferation of low cost wireless sensors, there is growing research interest in their applications, for example, in home healthcare and location tracking. However, due to sensors’ energy resource constraint, some possible applications of sensors have been restricted. In particular, in applications concerning deployment of mobile sensors in dynamic environments, high amounts of energy are consumed by sensors to maintain routing tables. Although existing methods have been proposed to query data from sensors without the use of any routing tables, these methods typically require redundant data to be sent back to the sink and not all of the aggregation functions could be executed precisely. In this paper, we modify an existing method to provide more accurate query answers and extend the lifetime of a wireless sensor network (WSN). According to our simulation, this method outperforms the existing method our approach modifies.
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V.S., Krushnasamy, Pravin Prakash Adivarekar, Deepa G, Mohammed Azam, and Prince Williams. "MEMS-ENHANCED SENSOR FUSION FOR AUTONOMOUS NAVIGATION IN ROBOTICS." ICTACT Journal on Microelectronics 9, no. 3 (2023): 1607–12. https://doi.org/10.21917/ijme.2023.0279.

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In autonomous robotics, achieving precise navigation remains a formidable challenge, necessitating advancements in sensor fusion techniques. This study addresses the pivotal role of Micro-Electro-Mechanical Systems (MEMS) in enhancing sensor fusion for autonomous navigation. The pressing problem of achieving accurate and real-time navigation in dynamic environments has spurred the need for innovative solutions. The existing literature reveals a research gap in the seamless integration of MEMS sensors for robust navigation. While traditional sensor fusion methods often face limitations in handling diverse and rapidly changing environmental conditions, MEMS offer a promising avenue for overcoming these challenges. The miniature size, low power consumption, and high sensitivity of MEMS sensors make them ideal candidates for providing rich and reliable data for navigation purposes. The method employed in this research involves a comprehensive integration of MEMS sensors, such as accelerometers, gyroscopes, and magnetometers, into a unified sensor fusion framework. This framework leverages advanced algorithms to intelligently combine data from multiple sensors, mitigating individual sensor limitations and enhancing overall accuracy. The integration of MEMS sensors aims to provide a more holistic understanding of the robot surroundings, facilitating improved decision-making in navigation tasks. The results of our study showcase a significant improvement in the accuracy and efficiency of autonomous navigation in dynamic environments. MEMS-enhanced sensor fusion proves to be a viable solution for addressing the challenges posed by unpredictable terrains and obstacles. The robot equipped with MEMS sensors demonstrates enhanced adaptability and responsiveness, showcasing the potential for real-world applications.
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Dissertations / Theses on the topic "Sensors on dynamic environments"

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Nicholson, Ann Elizabeth. "Monitoring discrete environments using dynamic belief networks." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.306008.

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Westerlund, Andreas. "Sensor-Based Trajectory Planning in Dynamic Environments." Thesis, Linköpings universitet, Reglerteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-150040.

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Motion planning is central to the efficient operation and autonomy of robots in the industry. Generally, motion planning of industrial robots is treated in a two-step approach. First, a geometric path between the start and goal position is planned where the objective is to achieve as short path as possible together with avoiding obstacles. Alternatively, a pre-defined geometric path is provided by the end user. Second, the velocity profile along the geometric path is calculated accounting for system dynamics together with other constraints. This approach is computationally efficient, but yield sub-optimal solutions as the system dynamics is not considered in the first step when the geometric path is planned. In this thesis, an alternative to the two-step approach is investigated and a trajectory planner is designed and implemented which plans both the geometric path and the velocity profile simultaneously. The motion planning problem is formulated as an optimal control problem, which is solved by a direct collocation method where the trajectory is parametrised by splines, and the spline nodes and knots are used as optimization variables. The implemented trajectory planner is evaluated in simulations, where the planner is applied to a simple planar elbow robot and ABB's SCARA robot IRB 910SC. Trade-off between computation time and optimality is identified and the results indicate that the trajectory planner yields satisfactory solutions. On the other hand, the simulations indicate that it is not possible to apply the proposed method on a real robot in real-time applications without significant modifications in the implementation to decrease the computation time.
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Wei, Pihui. "Dynamic Bug Detection in TinyOS Operating Environments." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1238166929.

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Pizzocaro, Diego. "Instantaneous multi-sensor task allocation in static and dynamic environments." Thesis, Cardiff University, 2011. http://orca.cf.ac.uk/31333/.

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A sensor network often consists of a large number of sensing devices of different types. Upon deployment in the field, these sensing devices form an ad hoc network using wireless links or cables to communicate with each other. Sensor networks are increasingly used to support emergency responders in the field usually requiring many sensing tasks to be supported at the same time. By a sensing task we mean any job that requires some amount of sensing resources to be accomplished such as localizing persons in need of help or detecting an event. Tasks might share the usage of a sensor, but more often compete to exclusively control it because of the limited number of sensors and overlapping needs with other tasks. Sensors are in fact scarce and in high demand. In such cases, it might not be possible to satisfy the requirements of all tasks using available sensors. Therefore, the fundamental question to answer is: “Which sensor should be allocated to which task?", which summarizes the Multi-Sensor Task Allocation (MSTA) problem. We focus on a particular MSTA instance where the environment does not provide enough information to plan for future allocations constraining us to perform instantaneous allocation. We look at this problem in both static setting, where all task requests from emergency responders arrive at once, and dynamic setting, where tasks arrive and depart over time. We provide novel solutions based on centralized and distributed approaches. We evaluate their performance using mainly simulations on randomly generated problem instances; moreover, for the dynamic setting, we consider also feasibility of deploying part of the distributed allocation system on user mobile devices. Our solutions scale well with different number of task requests and manage to improve the utility of the network, prioritizing the most important tasks.
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Barrow, Alastair. "Improved haptic interaction for large workspace, multi-sensory, dynamic virtual environments." Thesis, University of Reading, 2010. http://centaur.reading.ac.uk/24825/.

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Virtual Reality (VR) is a rapidly advancing scientific field which enables humans to experience environments other than that which they physically inhabit. Humans use all their senses to interact in the real world and there should be no difference when using VR. This thesis explores the current state-of-the-art in Multi-Sensory Virtual Reality (MSVR) and presents new techniques for improving the level of interaction and realism in touch enabled MSVR. It is shown that, of the three senses which are commonly included in MSVR: vision, audition and haptics (touch), haptics is the least well represented. Further, it is observed that haptic interaction is particularly lacking in two areas: natural object manipulation and large workspace interaction. Object manipulation is limited by the number of contact points a haptic device can provide and there are both hardware and software challenges related to this. It is also limited by the realism of simulated object motion which is more complex for haptics than purely visual-auditory simulations. A novel haptic rendering algorithm, called the xFCA, has been designed to improve multi-finger manipulation of arbitrarily shaped objects. Also, a software platform known as MUSI has been developed which integrates the xFCA into a dynamic rigid-body simulator to allow the natural manipulation of virtual objects. The challenges in the development of MUSI, along with its advantages and limitations are discussed. Two new approaches to increasing the workspace of haptic devices have been investigated. The first, a novel haptic rendering technique which provides force feedback related to velocity is applied to a virtual shopping trolley. The second, a novel method of chaining devices together, is used to create a multi-finger haptic interface for both large and fast movements. Finally, both systems have been integrated into an MSVR simulator and the results of this are also discussed.
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Barbosa, Pedro. "Scalable wireless sensor networks for dynamic communication environments : simulation and modelling." Thesis, University of Southampton, 2011. https://eprints.soton.ac.uk/177575/.

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This thesis explores the deployment of Wireless Sensor Networks (WSNs) on localised maritime events. In particular, it will focus on the deployment of a WSN at sea and estimating what challenges derive from the environment and how they affect communication. This research addresses these challenges through simulation and modelling of communication and environment, evaluating the implications of hardware selection and custom algorithm development. The first part of this thesis consists of the analysis of aspects related to the Medium Access Control layer of the network stack in large-scale networks. These details are commonly hidden from upper layers, thus resulting in misconceptions of real deployment characteristics. Results show that simple solutions have greater advantages when the number of nodes within a cluster increases. The second part considers routing techniques, with focus on energy management and packet delivery. It is shown that, under certain conditions, relaying data can increase energy savings, while at the same time allows a more even distribution of its usage between nodes. The third part describes the development of a custom-made network simulator. It starts by considering realistic radio, channel and interference models to allow a trustworthy simulation of the deployment environment. The MAC and Routing techniques developed thus far are adapted to the simulator in a cross-layer manner. The fourth part consists of adapting the WSN behaviour to the variable weather and topology found in the chosen application scenario. By analysing the algorithms presented in this work, it is possible to find and use the best alternative under any set of environmental conditions. This mechanism, the environment-aware engine, uses both network and sensing data to optimise performance through a set of rules that involve message delivery and distance between origin and cluster head
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Taylor, Brian Kyle. "TRACKING FLUID-BORNE ODORS IN DIVERSE AND DYNAMIC ENVIRONMENTS USING MULTIPLE SENSORY MECHANISMS." Case Western Reserve University School of Graduate Studies / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=case1341601566.

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Jagolinzer, Scott R. "Design and Control of a Dynamic and Autonomous Trackless Vehicle Using Onboard and Environmental Sensors." FIU Digital Commons, 2017. http://digitalcommons.fiu.edu/etd/3173.

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The purpose of this thesis is to explore the current state of automated guided vehicles (AGVs), sensors available for the vehicles to be equipped with, control systems for the vehicles to run on, and wireless technology to connect the whole system together. With a technological push towards increasing automation and maximizing the possible throughput of systems, automated technology needs to improve for trackless and wireless systems such as vehicles that can be used to move loads in a vast array of applications. The goal of this research is to develop and propose improvements in both vehicle and control system design that allows for improved safety and efficiency. Right now the main issues are maneuverability of vehicles and control systems being adaptive enough to deal with connection issues between systems. While prolonged connection issues will result in a stoppage of operation of any system that relies on wireless communication, intermittent issues can also cause systems to have an emergency stop. I have looked into ways to offload tasks from the central system and allow the vehicles themselves to have more computational privileges such that they can operate in a semi-independent manner. The result is a proposed system that remedies or limits negative effects that currently cause issues with trackless vehicles and control systems working with remote systems that communicate via wireless means.
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Murphy, Taylor B. "Within Reach: The Contribution of Dynamic Viewpoint to the Perception of Remote Environments." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1500466996274077.

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Hegazy, Tamir A. "A Distributed Approach to Dynamic Autonomous Agent Placement for Tracking Moving Targets with Application to Monitoring Urban Environments." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/4901.

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The problem of dynamic autonomous agent placement for tracking moving targets arises in many real-life applications, such as rescue operations, security, surveillance, and reconnaissance. The objective of this thesis is to develop a distributed hierarchical approach to address this problem. After the approach is developed, it is tested on a number of urban surveillance scenarios. The proposed approach views the placement problem as a multi-tiered architecture entailing modules for low-level sensor data preprocessing and fusion, decentralized decision support, knowledge building, and centralized decision support. This thesis focuses upon the modules of decentralized decision support and knowledge building. The decentralized decision support module requires a great deal of coordination among agents to achieve the mission objectives. The module entails two classes of distributed algorithms: non-model-based algorithms and model-based algorithms. The first class is used as a place holder while a model is built to describe agents knowledge about target behaviors. After the model is built and evaluated, agents switch to the model-based algorithms. To apply the approach to urban environments, urban terrain zones are classified, and the problem is mathematically formulated for two different types of urban terrain, namely low-rise, widely spaced and high-rise, closely spaced zones. An instance of each class of algorithms is developed for each of the two types of urban terrain. The algorithms are designed to run in a distributed fashion to address scalability and fault tolerance issues. The class of model-based algorithms includes a distributed model-based algorithm for dealing with evasive targets. The algorithm is designed to improve its performance over time as it learns from past experience how to deal with evasive targets. Apart from the algorithms, a model estimation module is developed to build motion models online from sensor observations. The approach is evaluated through a set of simulation experiments inspired from real-life scenarios. Experimental results reveal the superiority of the developed algorithms over existing ones and the applicability of the online model-building method. Therefore, it is concluded that the overall distributed approach is capable of handling agent placement or surveillance applications in urban environments among other applications.
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Books on the topic "Sensors on dynamic environments"

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Walber, Chad, Matthew Stefanski, and Julie Harvie, eds. Sensors and Instrumentation, Aircraft/Aerospace and Dynamic Environments Testing, Volume 7. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-05415-0.

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Walber, Chad, Matthew Stefanski, and Steve Seidlitz, eds. Sensors and Instrumentation, Aircraft/Aerospace, Energy Harvesting & Dynamic Environments Testing, Volume 7. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-75988-9.

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Walber, Chad, Patrick Walter, and Steve Seidlitz, eds. Sensors and Instrumentation, Aircraft/Aerospace, Energy Harvesting & Dynamic Environments Testing, Volume 7. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-12676-6.

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Walber, Chad, Patrick Walter, and Steve Seidlitz, eds. Sensors and Instrumentation, Aircraft/Aerospace, Energy Harvesting & Dynamic Environments Testing, Volume 7. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-47713-4.

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Fujimura, Kikuo. Motion Planning in Dynamic Environments. Springer Japan, 1991.

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Laugier, Christian, and Raja Chatila, eds. Autonomous Navigation in Dynamic Environments. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73422-2.

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Dykes, Alan P., Mark Mulligan, and John Wainwright, eds. Monitoring and Modelling Dynamic Environments. John Wiley & Sons, Ltd, 2015. http://dx.doi.org/10.1002/9781118649596.

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Fujimura, Kikuo. Motion Planning in Dynamic Environments. Springer Japan, 1991. http://dx.doi.org/10.1007/978-4-431-68165-6.

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Branke, Jürgen. Evolutionary Optimization in Dynamic Environments. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0911-0.

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Branke, Jürgen. Evolutionary Optimization in Dynamic Environments. Springer US, 2002.

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Book chapters on the topic "Sensors on dynamic environments"

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Elhoseny, Mohamed, and Aboul Ella Hassanien. "Expand Mobile WSN Coverage in Harsh Environments." In Dynamic Wireless Sensor Networks. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92807-4_2.

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Elhoseny, Mohamed, and Aboul Ella Hassanien. "Mobile Object Tracking in Wide Environments Using WSNs." In Dynamic Wireless Sensor Networks. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92807-4_1.

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Elhoseny, Mohamed, and Aboul Ella Hassanien. "Extending Homogeneous WSN Lifetime in Dynamic Environments Using the Clustering Model." In Dynamic Wireless Sensor Networks. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92807-4_4.

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Wang, Ying, Daniel Ewert, Tobias Meisen, Daniel Schilberg, and Sabina Jeschke. "Work Area Monitoring in Dynamic Environments Using Multiple Auto-aligning 3D Sensors." In Automation, Communication and Cybernetics in Science and Engineering 2013/2014. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08816-7_62.

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Erben, Andreas, Alexander Geist, Immanuel Voigt, et al. "Smart Pressure Film Sensor for Machine Tool Optimization and Characterization of the Dynamic Pressure Field on Machine Surfaces." In Lecture Notes in Production Engineering. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-34486-2_14.

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AbstractKnowledge of thermal interactions with the environment is essential for improving the performance of machine tools. Therefore, it is necessary to detect and quantify the convective heat flows at machine tool surfaces, that occur in the workspace as a result of cutting fluid use or outside the machine due to active air flow. Thin-film sensors made of shape memory alloys with integrated small temperature sensors are suitable for detecting very fine pressure differences and can be used to estimate convective heat transfer. By measuring the pressure differences, the dynamic pressure field at the surface can be determined. Since the pressure field correlates with the flow field, conclusions can be drawn about the flow velocity. This leads to more profound and extended possibilities to match flow fields from CFD simulations with measured data. At the same time, the surface temperature is also recorded by this sensor. Reference measurements of the temperature in the free flow are used to characterize the heat transfer. By knowing the pressures, temperatures and the correlating flow velocity near the wall, the heat transfer coefficient can be determined. Against this background, this paper demonstrates the behavior of shape memory alloys as fluid pressure sensors and addresses the development of such sensors for machine tools. For this purpose, sensor units are to be developed that can be placed as a sensor network (composite of several sensors on one surface) inside and outside the workspace.
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Mittal, Anurag, and Larry S. Davis. "Visibility Analysis and Sensor Planning in Dynamic Environments." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24670-1_14.

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Owens, Brian C., Randall L. Mayes, Moheimin Khan, D. Gregory Tipton, and Brandon Zwink. "Flight Environments Demonstrator: Part I—Experiment Design and Test Planning." In Sensors and Instrumentation, Aircraft/Aerospace, Energy Harvesting & Dynamic Environments Testing, Volume 7. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12676-6_29.

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Brauner, Yaron, Daniel Herfert, Andreas Lemke, and Maik Gollnick. "Acoustic Resonance Testing on Production Lines with the Smart Impulse Hammer WaveHitMAX." In Sensors and Instrumentation, Aircraft/Aerospace and Dynamic Environments Testing, Volume 7. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05415-0_6.

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Buck, David T. "Test Data Measurement Uncertainty Analysis." In Sensors and Instrumentation, Aircraft/Aerospace and Dynamic Environments Testing, Volume 7. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05415-0_1.

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Schoenherr, Tyler F., David E. Soine, and Bryan L. Witt. "Experimental Modal Analysis of a Resonant Plate During a Mid-Field Pyroshock Replication Test." In Sensors and Instrumentation, Aircraft/Aerospace and Dynamic Environments Testing, Volume 7. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05415-0_4.

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Conference papers on the topic "Sensors on dynamic environments"

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Plozza, Davide, Steven Marty, Cyril Scherrer, Simon Schwartz, Stefan Zihlmann, and Michele Magno. "Autonomous Navigation in Dynamic Human Environments with an Embedded 2D LiDAR-based Person Tracker." In 2024 IEEE Sensors Applications Symposium (SAS). IEEE, 2024. http://dx.doi.org/10.1109/sas60918.2024.10636369.

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Su, Bolun, Huijie Feng, Chengyu Chen, Siwen Wang, and Yiming Shao. "Research on Submersible Search Models Adapted to Dynamic Environments and Multi-UUV Collaboration." In 2024 IEEE 2nd International Conference on Sensors, Electronics and Computer Engineering (ICSECE). IEEE, 2024. http://dx.doi.org/10.1109/icsece61636.2024.10729325.

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Lei, Jiajun, Jiaxiang Wei, and Zhihao Zhang. "SE(3) Pose Estimation for Simultaneous Localization of Objects and Sensors in Dynamic Environments." In 2024 3rd International Conference on Automation, Robotics and Computer Engineering (ICARCE). IEEE, 2024. https://doi.org/10.1109/icarce63054.2024.00039.

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Hurley, Michael F., Arvin Cunningham, Drew Lysne, Sanjeev Acharya, Brian J. Jaques, and Darryl P. Butt. "A Condition Monitor for Atmospheric Induced Stress Corrosion Cracking." In CORROSION 2018. NACE International, 2018. https://doi.org/10.5006/c2018-11634.

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Abstract A sacrificial sensor has been designed to detect the occurrence and rate of atmospheric corrosion and stress corrosion cracking. The sensor fixture was constructed using additive manufacturing and can be customized for use with small size wires or ribbons of any metallic material as a sensor electrode. Resistance change was used to monitor the degradation of arrays of small samples subjected to various stress and environmental conditions. Typical passive atmospheric corrosion sensors do not account for applied stress, or if they do, use statically loaded electrodes and stress relaxation during SCC precludes extended monitoring. However, this sensor allows for propagation of SCC to be monitored since the electrode experiences a dynamic applied stress. This low cost test system permits detection of degradation across multiple time and length scales and can be tailored for the intended application and environment. For proof of concept testing the sensor was used to detect corrosion and stress corrosion cracking of austenitic stainless steels exposed to liquid and high humidity corrosive environments.
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Grieve, Katharine F. "Live imaging of retinal cell dynamics with dynamic full field OCT (Conference Presentation)." In Optical Fibers and Sensors for Medical Diagnostics, Treatment, and Environmental Applications XXV, edited by Israel Gannot and Katy Roodenko. SPIE, 2025. https://doi.org/10.1117/12.3056010.

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S, Srivatzen, Kavitha BS, and Sundararajan Asokan. "SU-8 coated etched fiber Bragg grating sensors: A versatile platform for detection of any biomarker using antibody-antigen chemistry." In CLEO: Applications and Technology. Optica Publishing Group, 2024. http://dx.doi.org/10.1364/cleo_at.2024.jtu2a.184.

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Biomarker detection is pivotal in various fields, including healthcare, environmental monitoring, and biotechnology. This work introduces a versatile platform for biomarker detection by utilizing SU-8 negative photoresist coated etched Fiber Bragg Grating (eFBG) sensors in conjunction with antibody-antigen chemistry. The unique combination of FBG sensors and SU-8 coating offers several advantages, including enhanced sensitivity, selectivity, and versatility. In this study, we present the design and fabrication of SU-8 coated FBG sensors optimized for biomarker detection. The SU-8 coating not only provides a stable and biocompatible surface for immobilizing antibodies but also improves the sensor's response to specific antigen binding. As a proof of concept, the detection of concentration of standard antigen is demonstrated by functionalization of the SU-8 coated eFBG sensor with corresponding IgG antibody using EDC/NHS crosslinking chemistry. The reflected Bragg wavelength (lB) of the eFBG sensor is modulated by the added antigen concentration. The dynamic range of the sensor is from 8 pg/ml to 80 ng/ml with average sensitivity of 32.3 pm 10- 1 g-1 ml.
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de Alteriis, Giorgio, Giusiana Testa, Giulio Mariniello, et al. "Distributed Monitoring System for Dynamic Identification Based on MEMS Sensors." In 2024 IEEE International Workshop on Metrology for Living Environment (MetroLivEnv). IEEE, 2024. http://dx.doi.org/10.1109/metrolivenv60384.2024.10615522.

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Agnew, L., B. Clark, V. Avance, and F. Friedersdorf. "Effect of Dynamic Humidity on Environmental Cracking of an Aerospace Aluminum Alloy." In CONFERENCE 2022. AMPP, 2022. https://doi.org/10.5006/c2022-18015.

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Abstract This work explores the effect of humidity and galvanic coupling on the environmental assisted crack initiation and growth rate of high-strength aluminum alloys under static load. Varied relative humidity and temperature cycles, based on relevant aircraft service environments, are used to identify factors leading to peak crack growth rate for a sodium chloride salt chemistry. The influence of dynamic environmental conditions versus constant environmental conditions are being evaluated. Aerospace materials are galvanically coupled to the aluminum substrate to quantify the effect on initiation time and growth rate. Spring-actuated double cantilever beam test systems with continuous sensor monitoring are employed in atmospheric environments with smooth-notch samples to produce estimates of time to crack nucleation, crack length, crack growth rate, and crack tip stress intensity. Simultaneous zero resistance ammeter measurement of the corrosion currents between galvanically coupled aerospace materials and the aluminum samples improves understanding of the relationships between atmospheric environment and the electrochemical processes leading to crack initiation and growth. Results demonstrate clear differences between wetting and drying processes, with peaks in galvanic corrosion current observed during drying and smaller peaks observed during wetting. Peaks in crack growth rate are observed at moderate relative humidity during drying processes.
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Schoen, Marco P. "Dynamic Compensation of Intelligent Sensors." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-42275.

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Commercial sensors have generally, due to their own characteristics, some undesirable influences on the measured quantity and its precision. In particular, the dynamic characteristics can be reflected on to the measured quantity and lead to false or delayed interpretation of the underlying physical process. The quality and therefore the cost of the sensor is often tied with the dynamic performance of these instruments. Intelligent sensors are able to adapt to changing environments, calibrate themselves, and predict the pattern of the future signal. This paper presents algorithms to improve the dynamic performance of sensors, identify the dynamic characteristics of the sensor, and to predict the future pattern of the measured quantity. In particular, two inverse filters are proposed for the improvement of the sensors dynamic performance. One filter incorporates an optimal constant feedback gain that reduces the computational cost and increases the accuracy. A system identification method is used to identify the sensor’s dynamic properties and allows for adaptation of the inverse filter’s parameters. This identification algorithm computes the optimum input to the system i.e. the sensor. The optimization is based on the inverse correlation matrix of the information matrix. A genetic algorithm is used to perform both optimizations, for the computation of the optimal input, and for the optimal constant feedback gain. In addition, a predictive filter formulation is given that is based on the identified system. Simulation results indicate that both inverse filters are capable of recovering the original or true signal. The second filter shows superiority in terms of convergence, lower computational cost, and lower error due to its optimized parameters. The predictive filter indicates good working accuracy for the signal prediction.
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Zhao, Jianguo, and Ali Abbas. "A Low-Cost Soft Coiled Sensor for Soft Robots." In ASME 2016 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/dscc2016-9916.

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Soft robots made from soft materials can closely emulate biological system using simple soft mechanical structures. Compared with traditional rigid-link robots, they are safe to work with humans and can adapt to confined environments. As a result, they are widely used for various robotic locomotions and manipulations. Nevertheless, for soft robots, being able to sense its state to enable closed-loop control using soft sensors remains a challenge. Existing sensors include external sensors such as camera systems, electromagnetic tracking systems, and internal sensors such as optical fibers, conductive liquid, and carbon black filled strips. In this paper, we investigate a new soft sensor made from low-cost conductive nylon sewing threads. By continuously inserting twists into a thread under some weight, coils can be formed to enable a coiled soft sensor. The resistance of the sensor varies with the change of length. The fabrication and experiments for this new coiled sensor is described in this paper. Embedding this sensor to a 3D printed soft manipulator demonstrates the sensing capability. Compared to existing soft sensors, the coiled sensor is low-cost, easy to fabricate, and can also be used as an actuator. It can be embedded to any soft robot to measure the deformation for closed-loop feedback control.
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Reports on the topic "Sensors on dynamic environments"

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Ng, B., and W. Hanley. Towards Intelligent Dynamic Deployment of Mobile Sensors in Complex Resource-Bounded Environments. Office of Scientific and Technical Information (OSTI), 2007. http://dx.doi.org/10.2172/919953.

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Xiao, Hai, Hai-Lung Tsai, and Junhang Dong. Micro-Structured Sapphire Fiber Sensors for Simultaneous Measurements of High-T and Dynamic Gas Pressure in Harsh Environments. Office of Scientific and Technical Information (OSTI), 2014. http://dx.doi.org/10.2172/1171318.

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Niles, Kendall, Jason Ray, Kenneth Niles, Andrew Maxwell, and Anton Netchaev. Monitoring for analytes through LoRa and LoRaWAN technology. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49457.

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The purpose of this research is to investigate the use of a communication network utilizing Long Range (LoRa) low-power wide-area network protocol for the telemetry of detected target chemicals. The sensor platform under development allows traditional electrochemical techniques to be executed with a low Size, Weight, and Power (low SWaP) system that is deployable using an autonomous or remote-controlled vehicle. Once in the field, the sensors communicate target chemical concentrations to a centralized gateway through LoRa to an Internet of Things (IoT) network. Researchers are currently deploying the prototype network for field testing of each node's sensing, meshing, and communication capabilities throughout all weather climates. Developing a robust and dynamic sensor network to monitor the environment and provide a live data feed to detect chemicals of interest in the environment eliminates the need for direct human interaction. The low power consumption of LoRa allows the network nodes to be deployed for an extended amount of time on a single battery supply.
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detection, refractometer and a scale (mass). Data were analyzed and provided input for five classification models. Chlorophyll from fluorescence was found to give the best estimation for ripeness stage while the combination of machine vision and firmness from impact performed best for quality sorting. A new algorithm was developed to estimate and minimize training size for supervised classification. A new criteria was established to choose a training set such that a recurrent auto-associative memory neural network is stabilized. Moreover, this method provides for rapid and accurate updating of the classifier over growing seasons, production environments and cultivars. Different classification approaches (parametric and non-parametric) for grading were examined. Statistical methods were found to be as accurate as neural networks in grading. Classification models by voting did not enhance the classification significantly. A hybrid model that incorporated heuristic rules and either a numerical classifier or neural network was found to be superior in classification accuracy with half the required processing of solely the numerical classifier or neural network. In Israel: A multi-sensing approach utilizing non-destructive sensors was developed. Shape, color, stem identification, surface defects and bruises were measured using a color image processing system. Flavor parameters (sugar, acidity, volatiles) and ripeness were measured using a near-infrared system and an electronic sniffer. Mechanical properties were measured using three sensors: drop impact, resonance frequency and cyclic deformation. Classification algorithms for quality sorting of fruit based on multi-sensory data were developed and implemented. The algorithms included a dynamic artificial neural network, a back propagation neural network and multiple linear regression. Results indicated that classification based on multiple sensors may be applied in real-time sorting and can improve overall classification. Advanced image processing algorithms were developed for shape determination, bruise and stem identification and general color and color homogeneity. An unsupervised method was developed to extract necessary vision features. The primary advantage of the algorithms developed is their ability to learn to determine the visual quality of almost any fruit or vegetable with no need for specific modification and no a-priori knowledge. Moreover, since there is no assumption as to the type of blemish to be characterized, the algorithm is capable of distinguishing between stems and bruises. This enables sorting of fruit without knowing the fruits' orientation. A new algorithm for on-line clustering of data was developed. The algorithm's adaptability is designed to overcome some of the difficulties encountered when incrementally clustering sparse data and preserves information even with memory constraints. Large quantities of data (many images) of high dimensionality (due to multiple sensors) and new information arriving incrementally (a function of the temporal dynamics of any natural process) can now be processed. Furhermore, since the learning is done on-line, it can be implemented in real-time. The methodology developed was tested to determine external quality of tomatoes based on visual information. An improved model for color sorting which is stable and does not require recalibration for each season was developed for color determination. Excellent classification results were obtained for both color and firmness classification. Results indicted that maturity classification can be obtained using a drop-impact and a vision sensor in order to predict the storability and marketing of harvested fruits. In conclusion: We have been able to define quantitatively the critical parameters in the quality sorting and grading of both fresh market cantaloupes and tomatoes. We have been able to accomplish this using nondestructive measurements and in a manner consistent with expert human grading and in accordance with market acceptance. This research constructed and used large databases of both commodities, for comparative evaluation and optimization of expert system, statistical and/or neural network models. The models developed in this research were successfully tested, and should be applicable to a wide range of other fruits and vegetables. These findings are valuable for the development of on-line grading and sorting of agricultural produce through the incorporation of multiple measurement inputs that rapidly define quality in an automated manner, and in a manner consistent with the human graders and inspectors.
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Unzeta, Bruno Bueno, Jan de Boer, Ruben Delvaeye, et al. Review of lighting and daylighting control systems. IEA SHC Task 61, 2021. http://dx.doi.org/10.18777/ieashc-task61-2021-0003.

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There is a large number of control systems proposed either by lighting manufacturers or motor manufacturers for shading systems. In addition there are many other solutions proposed by specific manufacturers of Building Management Systems (BMS) or manufacturers of components to be installed in luminaires and switches, as well as in the electric lighting architecture (transformers, gateways to the internet, sensors, etc.). For many consumers -i.e.-the installer, the facility manager, or the final user (building occupant) – this forms a complex and dynamic market environment with high frequent changes, every year or even every month or day. In this report we aim to provide some basic strategic information, showing the status of the supply at the time this report was written (2019-2021). Although the market develops very fast, there are principles of controls which are rather independent of the progress of technology.
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Jelinek, Raz, Paul Dawson, Timothy Hanks, William Pennington, and Julie Northcutt. Bacterial sensors for food processing environments. United States Department of Agriculture, 2013. http://dx.doi.org/10.32747/2013.7598157.bard.

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The overall objective of this project was to develop a new bacterial contaminant sensor based upon polydiacetylene(PDA) which is a unique polymer that changes color and configuration in response to external molecular stimuli. While this polymer has been well studied and has been shown to respond to bacterial stimuli in the laboratory, application to food processing environments has not been demonstrated. One hurdle in the application of biosensors in a food processing environment is interference of food sanitizers with the detection of bacteria. Common food sanitizers were evaluated for their response to PDA and different concentrations paving the way for use of modified PDAs developed by the research team to be used in food plants. Further development of PDA bacterial sensors focused on simplifying its application by immobilizing PDA on cotton and paper for use on swabs, wipes and dip papers. Increasing the sensitivity of PDAs was investigated by attaching fluorophores. Future and continued work will include the decoration of PDAs with apatmers to improve the specificity of the biosensor to food pathogens.
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Bendikov, Michael, and Thomas C. Harmon. Development of Agricultural Sensors Based on Conductive Polymers. United States Department of Agriculture, 2006. http://dx.doi.org/10.32747/2006.7591738.bard.

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In this 1-year feasibility study, we tried polymerization of several different monomers, commercial as well as novel, specially designed and synthesized for this project in the presence of the nitrate ion to produce imprinted conductive polymers. Polymers 1 and 2 (shown below) produced a response to nitrate, but one inferior to that produced by a polypyrrole (Ppy)-based sensor (which we demonstrated prior to this study). Thus, we elected to proceed with improving the stability of the Ppy-based sensor. In order to improve stability of the Ppy-based sensor, we created a two-layer design which includes nitrate-doped Ppy as an inner layer, and nitrate-doped PEDOT as the outer layer. PEDOT is known for its high environmental stability and conductivity. This design has demonstrated promise, but is still undergoing optimization and stability testing. Previously we had failed to create nitrate-doped PEDOT in the absence of a Ppy layer. Nitrate-doped PEDOT should be very promising for sensor applications due to its high stability and exceptional sensing properties as we showed previously for sensing of perchlorate ions (by perchlorate-doped PEDOT). During this year, we have succeeded in preparing nitrate-doped PEDOT (4 below) by designing a new starting monomer (compound 3 below) for polymerization. We are currently testing this design for nitrate sensing. In parallel with the fabrication design studies, we fabricated and tested nitrate-doped Ppy sensors in a series of flow studies under laboratory and field conditions. Nitrate-doped Ppy sensors are less stable than is desirable but provide excellent nitrate sensing characteristics for the short-term experiments focusing on packaging and deployment strategies. The fabricated sensors were successfully interfaced with a commercial battery-powered self-logging (Onset Computer Hobo Datalogger) and a wireless data acquisition and transmission system (Crossbow Technologies MDA300 sensor interface and Mica2 wireless mote). In a series of flow-through experiments with water, the nitrate-doped Ppy sensors were exposed to pulses of dissolved nitrate and compared favorably with an expensive commercial sensor. In 24-hour field tests in both Merced and in Palmdale, CA agricultural soils, the sensors responded to introduced nitrate pulses, but with different dynamics relative to the larger commercial sensors. These experiments are on-going but suggest a form factor (size, shape) effect of the sensor when deployed in a porous medium such as soil. To fill the need for a miniature reference electrode, we identified and tested one commercial version (Cypress Systems, ESA Mini-reference electrode) which works well but is expensive ($190). To create an inexpensive miniature reference electrode, we are exploring the use of AgCl-coated silver wire. This electrode is not a “true” reference electrode; however, it can calibrated once versus a commercial reference electrode at the time of deployment in soil. Thus, only one commercial reference electrode would suffice to support a multiple sensor deployment.
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Teti, Christopher, John Blessinger, Kennan Hodovic, and Kyle Brindley. TRUST Sensors in Environments: Accelerometers (SEA) Report. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/2007333.

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Hansen, Jeff, Scott Hissam, B. C. Meyers, et al. Resource Allocation in Dynamic Environments. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada609913.

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Carpenter, Michael, and Sang-Hyun Oh. Heat-activated Plasmonic Chemical Sensors for Harsh Environments. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1253572.

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