| 1. |
- Ahmad, Naeem, et al.
(författare)
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Cost Optimization of a Sky Surveillance Visual Sensor Network
- 2012
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Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - Belgium : SPIE - International Society for Optical Engineering. - 9780819491299 ; , s. Art. no. 84370U-
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Konferensbidrag (refereegranskat)abstract
- A Visual Sensor Network (VSN) is a network of spatially distributed cameras. The primary difference between VSN and other type of sensor network is the nature and volume of information. A VSN generally consists of cameras, communication, storage and central computer, where image data from multiple cameras is processed and fused. In this paper, we use optimization techniques to reduce the cost as derived by a model of a VSN to track large birds, such as Golden Eagle, in the sky. The core idea is to divide a given monitoring range of altitudes into a number of sub-ranges of altitudes. The sub-ranges of altitudes are monitored by individual VSNs, VSN1 monitors lower range, VSN2 monitors next higher and so on, such that a minimum cost is used to monitor a given area. The VSNs may use similar or different types of cameras but different optical components, thus, forming a heterogeneous network. We have calculated the cost required to cover a given area by considering an altitudes range as single element and also by dividing it into sub-ranges. To cover a given area with given altitudes range, with a single VSN requires 694 camera nodes in comparison to dividing this range into sub-ranges of altitudes, which requires only 96 nodes, which is 86% reduction in the cost.
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| 2. |
- Ahmad, Naeem, et al.
(författare)
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Model and placement optimization of a sky surveillance visual sensor network
- 2011
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Ingår i: Proceedings - 2011 International Conference on Broadband and Wireless Computing, Communication and Applications, BWCCA 2011. - : IEEE Computer Society. - 9781457714559 ; , s. 357-362
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Konferensbidrag (refereegranskat)abstract
- Visual Sensor Networks (VSNs) are networks which generate two dimensional data. The major difference between VSN and ordinary sensor network is the large amount of data. In VSN, a large number of camera nodes form a distributed system which can be deployed in many potential applications. In this paper we present a model of the physical parameters of a visual sensor network to track large birds, such as Golden Eagle, in the sky. The developed model is used to optimize the placement of the camera nodes in the VSN. A camera node is modeled as a function of its field of view, which is derived by the combination of the lens focal length and camera sensor. From the field of view and resolution of the sensor, a model for full coverage between two altitude limits has been developed. We show that the model can be used to minimize the number of sensor nodes for any given camera sensor, by exploring the focal lengths that both give full coverage and meet the minimum object size requirement. For the case of large bird surveillance we achieve 100% coverage for relevant altitudes using 20 camera nodes per km2 for the investigated camera sensors.
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| 3. |
- Ahmad, Naeem, et al.
(författare)
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Model, placement optimization and verification of a sky surveillance visual sensor network
- 2013
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Ingår i: International Journal of Space-Based and Situated Computing (IJSSC). - 2044-4893 .- 2044-4907. ; 3:3, s. 125-135
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Tidskriftsartikel (refereegranskat)abstract
- A visual sensor network (VSN) is a distributed system of a large number of camera nodes, which generates two dimensional data. This paper presents a model of a VSN to track large birds, such as golden eagle, in the sky. The model optimises the placement of camera nodes in VSN. A camera node is modelled as a function of lens focal length and camera sensor. The VSN provides full coverage between two altitude limits. The model can be used to minimise the number of sensor nodes for any given camera sensor, by exploring the focal lengths that fulfils both the full coverage and minimum object size requirement. For the case of large bird surveillance, 100% coverage is achieved for relevant altitudes using 20 camera nodes per km² for the investigated camera sensors. A real VSN is designed and measurements of VSN parameters are performed. The results obtained verify the VSN model.
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| 4. |
- Ahmad, Naeem, et al.
(författare)
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Modeling and Verification of a Heterogeneous Sky Surveillance Visual Sensor Network
- 2013
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Ingår i: International Journal of Distributed Sensor Networks. - : SAGE Publications. - 1550-1329 .- 1550-1477. ; , s. Art. id. 490489-
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Tidskriftsartikel (refereegranskat)abstract
- A visual sensor network (VSN) is a distributed system of a large number of camera nodes and has useful applications in many areas. The primary difference between a VSN and an ordinary scalar sensor network is the nature and volume of the information. In contrast to scalar sensor networks, a VSN generates two-dimensional data in the form of images. In this paper, we design a heterogeneous VSN to reduce the implementation cost required for the surveillance of a given area between two altitude limits. The VSN is designed by combining three sub-VSNs, which results in a heterogeneous VSN. Measurements are performed to verify full coverage and minimum achieved object image resolution at the lower and higher altitudes, respectively, for each sub-VSN. Verification of the sub-VSNs also verifies the full coverage of the heterogeneous VSN, between the given altitudes limits. Results show that the heterogeneous VSN is very effective to decrease the implementation cost required for the coverage of a given area. More than 70% decrease in cost is achieved by using a heterogeneous VSN to cover a given area, in comparison to homogeneous VSN. © 2013 Naeem Ahmad et al.
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| 5. |
- Ahmad, Naeem, et al.
(författare)
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Solution space exploration of volumetric surveillance using a general taxonomy
- 2013
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Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE. - 9780819495044 ; , s. Art. no. 871317-
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Konferensbidrag (refereegranskat)abstract
- Visual surveillance systems provide real time monitoring of the events or the environment. The availability of low cost sensors and processors has increased the number of possible applications of these kinds of systems. However, designing an optimized visual surveillance system for a given application is a challenging task, which often becomes a unique design task for each system. Moreover, the choice of components for a given surveillance application out of a wide spectrum of available alternatives is not an easy job. In this paper, we propose to use a general surveillance taxonomy as a base to structure the analysis and development of surveillance systems. We demonstrate the proposed taxonomy for designing a volumetric surveillance system for monitoring the movement of eagles in wind parks aiming to avoid their collision with wind mills. The analysis of the problem is performed based on taxonomy and behavioral and implementation models are identified to formulate the solution space for the problem. Moreover, we show that there is a need for generalized volumetric optimization methods for camera deployment.
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| 6. |
- Anwar, Qaiser, et al.
(författare)
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Intelligence Partitioning as a Method for Architectural Exploration of Wireless Sensor Node
- 2016
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Ingår i: Proceedings of the International Conference on Computational Science and Computational Intelligence (CSCI), 2016.. - : IEEE Press. - 9781509055104 ; , s. 935-940
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Konferensbidrag (refereegranskat)abstract
- Embedded systems with integrated sensing, processing and wireless communication are driving future connectivity concepts such as Wireless Sensor Networks (WSNs) and Internet of Things (IoTs). Because of resource limitations, there still exists a number of challenges such as low latency and energy consumption to realize these concepts to full potential. To address and understand these challenges, we have developed and employed an intelligence partitioning method which generates different implementation alternatives by distributing processing load across multiple nodes. The task-to-node mapping has exponential complexity which is hard to compute for a large scale system. Regarding this, our method provides recommendation to handle and minimize such complexity for a large system. Experiments on a use-case concludes that the proposed method is able to identify unfavourable architecture solutions in which forward and backword communication paths exists in task-to-node mapping. These solution can be avoided for further architectural exploration, thus limiting the space for architecture exploration of a sensor node.
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| 7. |
- Gatner, Ola, et al.
(författare)
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Method for Capturing Measured LiDAR Data with Ground Truth for Generation of Big Real LiDAR Data Sets
- 2024
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Ingår i: Conference Record - IEEE Instrumentation and Measurement Technology Conference. - : IEEE conference proceedings. - 9798350380903
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Konferensbidrag (refereegranskat)abstract
- The development of machine learning has resulted in data gaining a pivotal role in the technological advancement, especially data where the ground truth of targeted parameters can be efficiently captured. This requires the development of methods that facilitate accurate data collection with ground truth. Under this perspective, Time of Flight sensors pose a high complexity due to the multifaceted nature of noise in the captured data. To enable the use of such sensors in a wide range of applications including Artificial Intelligence, we need to provide also accurate ground truth data. In this article, we present a method for automated data capturing from a LiDAR sensor together with ground truth data generation. This method will facilitate generating big datasets from LiDAR sensors with high accuracy ground truth data. In addition, we provide a dataset that aside from depth sensor data contains also RGB, confidence and infrared data captured from the LiDAR sensor. As a result, the proposed method not only facilitates data capturing but it enables to generate accurate ground truth data, with RMSE of only 0.04 m at 1.3 m distance.
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| 8. |
- Imran, Muhammad, et al.
(författare)
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Analysis and Characterization of Embedded Vision Systems for Taxonomy Formulation
- 2013
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Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - USA : SPIE - International Society for Optical Engineering. - 9780819494290 ; , s. Art. no. 86560J-
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Konferensbidrag (refereegranskat)abstract
- The current trend in embedded vision systems is to propose bespoke solutions for specific problems as each application has different requirement and constraints. There is no widely used model or benchmark which aims to facilitate generic solutions in embedded vision systems. Providing such model is a challenging task due to the wide number of use cases, environmental factors, and available technologies. However, common characteristics can be identified to propose an abstract model. Indeed, the majority of vision applications focus on the detection, analysis and recognition of objects. These tasks can be reduced to vision functions which can be used to characterize the vision systems. In this paper, we present the results of a thorough analysis of a large number of different types of vision systems. This analysis led us to the development of a system’s taxonomy, in which a number of vision functions as well as their combination characterize embedded vision systems. To illustrate the use of this taxonomy, we have tested it against a real vision system that detects magnetic particles in a flowing liquid to predict and avoid critical machinery failure. The proposed taxonomy is evaluated by using a quantitative parameter which shows that it covers 95 percent of the investigated vision systems and its flow is ordered for 60 percent systems. This taxonomy will serve as a tool for classification and comparison of systems and will enable the researchers to propose generic and efficient solutions for same class of systems.
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| 9. |
- Imran, Muhammad, et al.
(författare)
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Architecture Exploration Based on Tasks Partitioning Between Hardware, Software and Locality for a Wireless Vision Sensor Node
- 2012
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Ingår i: International Journal of Distributed Systems and Technologies. - IGI Global, USA. : IGI Global. - 1947-3532 .- 1947-3540. ; 3:2, s. 58-71
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Tidskriftsartikel (refereegranskat)abstract
- Wireless Vision Sensor Networks (WVSNs) is an emerging field which consists of a number of Visual Sensor Nodes (VSNs). Compared to traditional sensor networks, WVSNs operates on two dimensional data, which requires high bandwidth and high energy consumption. In order to minimize the energy consumption, the focus is on finding energy efficient and programmable architectures for the VSN by partitioning the vision tasks among hardware (FPGA), software (Micro-controller) and locality (sensor node or server). The energy consumption, cost and design time of different processing strategies is analyzed for the implementation of VSN. Moreover, the processing energy and communication energy consumption of VSN is investigated in order to maximize the lifetime. Results show that by introducing a reconfigurable platform such as FPGA with small static power consumption and by transmitting the compressed images after pixel based tasks from the VSN results in longer battery lifetime for the VSN.
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| 10. |
- Imran, Muhammad, et al.
(författare)
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Architecture of Wireless Visual Sensor Node with Region of Interest Coding
- 2012
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Ingår i: Proceedings - 2012 IEEE 3rd International Conference on Networked Embedded Systems for Every Application, NESEA 2012. - : IEEE conference proceedings. - 9781467347235 ; , s. Art. no. 6474029-
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Konferensbidrag (refereegranskat)abstract
- The challenges involved in designing a wirelessVision Sensor Node include the reduction in processing andcommunication energy consumption, in order to maximize itslifetime. This work presents an architecture for a wireless VisionSensor Node, which consumes low processing andcommunication energy. The processing energy consumption isreduced by processing lightweight vision tasks on the VSN andby partitioning the vision tasks between the wireless VisionSensor Node and the server. The communication energyconsumption is reduced with Region Of Interest coding togetherwith a suitable bi-level compression scheme. A number ofdifferent processing strategies are investigated to realize awireless Vision Sensor Node with a low energy consumption. Theinvestigation shows that the wireless Vision Sensor Node, usingRegion Of Interest coding and CCITT group4 compressiontechnique, consumes 43 percent lower processing andcommunication energy as compared to the wireless Vision SensorNode implemented without Region Of Interest coding. Theproposed wireless Vision Sensor Node can achieve a lifetime of5.4 years, with a sample period of 5 minutes by using 4 AAbatteries.
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