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1.	Ahmad, Naeem, et al. (författare) Cost Optimization of a Sky Surveillance Visual Sensor Network 2012 Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - Belgium : SPIE - International Society for Optical Engineering. - 9780819491299 ; , s. Art. no. 84370U- 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.
2.	Ahmad, Naeem, et al. (författare) Model and placement optimization of a sky surveillance visual sensor network 2011 Ingår i: Proceedings - 2011 International Conference on Broadband and Wireless Computing, Communication and Applications, BWCCA 2011. - : IEEE Computer Society. - 9781457714559 ; , s. 357-362 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.
3.	Ahmad, Naeem, et al. (författare) Model, placement optimization and verification of a sky surveillance visual sensor network 2013 Ingår i: International Journal of Space-Based and Situated Computing (IJSSC). - 2044-4893 .- 2044-4907. ; 3:3, s. 125-135 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.
4.	Ahmad, Naeem, et al. (författare) Modeling and Verification of a Heterogeneous Sky Surveillance Visual Sensor Network 2013 Ingår i: International Journal of Distributed Sensor Networks. - : SAGE Publications. - 1550-1329 .- 1550-1477. ; , s. Art. id. 490489- 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.
5.	Ahmad, Naeem, et al. (författare) Solution space exploration of volumetric surveillance using a general taxonomy 2013 Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE. - 9780819495044 ; , s. Art. no. 871317- 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.
6.	Gustafsson, Oscar, et al. (författare) Generalized overlapping digit patterns for multi-dimensional sub-expression sharing 2010 Ingår i: 1st International Conference on Green Circuits and Systems, ICGCS 2010. - : IEEE conference proceedings. - 9781424468775 ; , s. 65-68 Konferensbidrag (refereegranskat)abstract Sub-expression sharing is a technique that can be applied to reduce the complexity of linear time-invariant non-recursive computations by identifying common patterns. It has recently been proposed that it is possible to improve the performance of single and multiple constant multiplication by identifying overlapping digit patterns. In this work we extend the concept of overlapping digit patterns to arbitrary shift dimensions, such as shift in time (FIR filters). Â© 2010 IEEE.
7.	Imran, Muhammad, et al. (författare) Analysis and Characterization of Embedded Vision Systems for Taxonomy Formulation 2013 Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - USA : SPIE - International Society for Optical Engineering. - 9780819494290 ; , s. Art. no. 86560J- 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.
8.	Imran, Muhammad, et al. (författare) Architecture Exploration Based on Tasks Partitioning Between Hardware, Software and Locality for a Wireless Vision Sensor Node 2012 Ingår i: International Journal of Distributed Systems and Technologies. - IGI Global, USA. : IGI Global. - 1947-3532 .- 1947-3540. ; 3:2, s. 58-71 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.
9.	Imran, Muhammad, et al. (författare) Architecture of Wireless Visual Sensor Node with Region of Interest Coding 2012 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- 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.
10.	Imran, Muhammad, et al. (författare) Complexity Analysis of Vision Functions for Comparison of Wireless Smart Cameras 2014 Ingår i: International Journal of Distributed Sensor Networks. - : SAGE Publications. - 1550-1329 .- 1550-1477. ; , s. Art. no. 710685- Tidskriftsartikel (refereegranskat)abstract There are a number of challenges caused by the large amount of data and limited resources such as memory, processing capability, energy consumption, and bandwidth, when implementing vision systems on wireless smart cameras using embedded platforms. It is usual for research in this field to focus on the development of a specific solution for a particular problem. There is a requirement for a tool which facilitates the complexity estimation and comparison of wireless smart camera systems in order to develop efficient generic solutions. To develop such a tool, we have presented, in this paper, a complexity model by using a system taxonomy. In this model, we have investigated the arithmetic complexity and memory requirements of vision functions with the help of system taxonomy. To demonstrate the use of the proposed model, a number of actual systems are analyzed in a case study. The complexity model, together with system taxonomy, is used for the complexity estimation of vision functions and for a comparison of vision systems. After comparison, the systems are evaluated for implementation on a single generic architecture. The proposed approach will assist researchers in benchmarking and will assist in proposing efficient generic solutions for the same class of problems with reduced design and development costs.
11.	Imran, Muhammad, et al. (författare) Complexity Analysis of Vision Functions for implementation of Wireless Smart Cameras using System Taxonomy 2012 Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - Belgium : SPIE - International Society for Optical Engineering. - 9780819491299 ; , s. Art. no. 84370C- Konferensbidrag (refereegranskat)abstract There are a number of challenges caused by the large amount of data and limited resources such as memory, processing capability, energy consumption and bandwidth when implementing vision systems on wireless smart cameras using embedded platforms. It is usual for research in this field to focus on the development of a specific solution for a particular problem. There is a requirement for a tool which has the ability to predict the resource requirements for the development and comparison of vision solutions in wireless smart cameras. To accelerate the development of such tool, we have used a system taxonomy, which shows that the majority of wireless smart cameras have common functions. In this paper, we have investigated the arithmetic complexity and memory requirements of vision functions by using the system taxonomy and proposed an abstract complexity model. To demonstrate the use of this model, we have analysed a number of implemented systems with this model and showed that complexity model together with system taxonomy can be used for comparison and generalization of vision solutions. Moreover, it will assist researchers/designers to predict the resource requirements for different class of vision systems in a reduced time and which will involve little effort.
12.	Imran, Muhammad, et al. (författare) Exploration of Target Architecture for aWireless Camera Based Sensor Node 2010 Ingår i: 28th Norchip Conference, NORCHIP 2010. - : IEEE conference proceedings. - 9781424489732 ; , s. 1-4 Konferensbidrag (refereegranskat)abstract The challenges associated with wireless vision sensor networks are low energy consumption, less bandwidth and limited processing capabilities. In order to meet these challenges different approaches are proposed. Research in wireless vision sensor networks has been focused on two different assumptions, first is sending all data to the central base station without local processing, second approach is based on conducting all processing locally at the sensor node and transmitting only the final results. Our research is focused on partitioning the vision processing tasks between Senor node and central base station. In this paper we have added the exploration dimension to perform some of the vision tasks such as image capturing, background subtraction, segmentation and Tiff Group4 compression on FPGA while communication on microcontroller. The remaining vision processing tasks i.e. morphology, labeling, bubble remover and classification are processed on central base station. Our results show that the introduction of FPGA for some of the visual tasks will result in a longer life time for the visual sensor node while the architecture is still programmable.
13.	Imran, Muhammad, et al. (författare) Implementation of wireless Vision Sensor Node for Characterization of Particles in Fluids 2012 Ingår i: IEEE transactions on circuits and systems for video technology (Print). - 1051-8215 .- 1558-2205. ; 22:11, s. 1634-1643 Tidskriftsartikel (refereegranskat)abstract Wireless Vision Sensor Networks (WVSNs) have a number of wireless Vision Sensor Nodes (VSNs), often spread over a large geographical area. Each node has an image capturing unit, a battery or alternative energy source, a memory unit, a light source, a wireless link and a processing unit. The challenges associated with WVSNs include low energy consumption, low bandwidth, limited memory and processing capabilities. In order to meet these challenges, our research is focused on the exploration of energy efficient reconfigurable architectures for VSN. In this work, the design/research challenges associated with the implementation of VSN on different computational platforms such as micro-controller, FPGA and server, are explored. In relation to this, the effect on the energy consumption and the design complexity at the node, when the functionality is moved from one platform to another are analyzed. Based on the implementation of the VSN on embedded platforms, the lifetime of the VSN is predicted using the measured energy values of the platforms for different implementation strategies. The implementation results show that an architecture, where the compressed images after pixel based operation are transmitted, realize a WVSN system with low energy consumption. Moreover, the complex post processing tasks are moved to a server, with reduced constraints.
14.	Imran, Muhammad, et al. (författare) Implementation of Wireless Vision Sensor Node With a Lightweight Bi-Level Video Coding 2013 Ingår i: IEEE Journal on Emerging and Selected Topics in Circuits and Systems. - : IEEE Press. - 2156-3357 .- 2156-3365. ; 3:2, s. 198-209 Tidskriftsartikel (refereegranskat)abstract Wireless vision sensor networks (WVSNs) consist ofa number of wireless vision sensor nodes (VSNs) which have limitedresources i.e., energy, memory, processing, and wireless bandwidth.The processing and communication energy requirements ofindividual VSN have been a challenge because of limited energyavailability. To meet this challenge, we have proposed and implementeda programmable and energy efficient VSN architecturewhich has lower energy requirements and has a reduced designcomplexity. In the proposed system, vision tasks are partitionedbetween the hardware implemented VSN and a server. The initialdata dominated tasks are implemented on the VSN while thecontrol dominated complex tasks are processed on a server. Thisstrategy will reduce both the processing energy consumption andthe design complexity. The communication energy consumption isreduced by implementing a lightweight bi-level video coding on theVSN. The energy consumption is measured on real hardware fordifferent applications and proposed VSN is compared against publishedsystems. The results show that, depending on the application,the energy consumption can be reduced by a factor of approximately1.5 up to 376 as compared to VSN without the bi-level videocoding. The proposed VSN offers energy efficient, generic architecturewith smaller design complexity on hardware reconfigurableplatform and offers easy adaptation for a number of applicationsas compared to published systems.
15.	Imran, Muhammad, et al. (författare) Low Complexity Background Subtraction for Wireless Vision Sensor Node 2013 Ingår i: Proceedings - 16th Euromicro Conference on Digital System Design, DSD 2013. - 9780769550749 ; , s. 681-688 Konferensbidrag (refereegranskat)abstract Wireless vision sensor nodes consist of limited resources such as energy, memory, wireless bandwidth and processing. Thus it becomes necessary to investigate lightweight vision tasks. To highlight the foreground objects, many machine vision applications depend on the background subtraction technique. Traditional background subtraction approaches employ recursive and non-recursive techniques and store the whole image in memory. This raises issues like complexity on hardware platform, energy requirements and latency. This work presents a low complexity background subtraction technique for a hardware implemented VSN. The proposed technique utilizes existing image scaling techniques for scaling down the image. The downscaled image is stored in memory of microcontroller which is already there for transmission. For subtraction operation, the background pixels are generated in real time through up scaling. The performance, and memory requirements of the system is compared for four image scaling techniques including nearest neighbor, averaging, bilinear, and bicubic. The results show that a system with lightweight scaling techniques, i.e., nearest neighbor and averaging, up to a scaling factor of 8, missed on average less than one object as compared to a system which uses a full original background image. The proposed approach will reduce the cost, design/implementation complexity and the memory requirement by a factor of up to 64.
16.	Imran, Muhammad, et al. (författare) On the number representation in sub-expression sharing 2010 Ingår i: International Conference on Signals and Electronic Systems, ICSES'10 - Conference Proceeding 2010. - : IEEE conference proceedings. - 9788390474342 ; , s. 17-20 Konferensbidrag (refereegranskat)abstract The core of many DSP tasks is Multiplication ofone data with several constants, i.e. in Digital filtering, image processing DCT and DFT. The Modern Portable equipments like Cellular phones and MP3 players which has DSP circuits,involve large number of multiplications of one variable with several constants (MCM) which leads to large area, delay and energy consumption in hardware. Multiplication operation can be realized using addition/subtraction and shifts without general multipliers. Different number representations are used in MCM algorithms and there are differnet views about different representations. Some of the authors termed the Canonic Signed Digit (CSD) representation as better for subexpression sharing. We have compared the results of CSD and Binary representations using our Generalized MCM Algorithm on Random Matrices and come to conclusion that binary representation is better compared to CSD when a system has multiple inputs and multiple outputs.
17.	Khursheed, Khursheed, et al. (författare) Analysis of change coding for data reduction in wireless visual sensor network Annan publikation (övrigt vetenskapligt/konstnärligt)
18.	Khursheed, Khursheed, et al. (författare) Bi-Level Video Codec for Machine Vision Embedded Applications 2013 Ingår i: Elektronika Ir Elektrotechnika. - : Kaunas University of Technology (KTU). - 1392-1215. ; 19:8, s. 93-96 Tidskriftsartikel (refereegranskat)abstract Wireless Visual Sensor Networks (WVSN) are feasible today due to the advancement in many fields of electronics such as Complementary Metal Oxide Semiconductor (CMOS) cameras, low power electronics, distributed computing and radio transceivers. The energy budget in WVSN is limited due to the small form factor of the Visual Sensor Nodes (VSNs) and the wireless nature of the application. The images captured by VSN contain huge amount of data which leads to high communication energy consumptions. Hence there is a need for designing efficient algorithms which are computationally less complex and provide high compression ratio. The change coding and Region of Interest (ROIs) coding are the options for data reduction of the VSN. But, for higher number of objects in the images, the compression efficiency of both the change coding and ROI coding becomes worse than that of image coding. This paper explores the compression efficiency of the Bi-Level Video Codec (BVC) for several representative machine vision applications. We proposed to implement image coding, change coding and ROI coding at the VSN and to select the smallest bit stream among the three. Results show that the compression performance of the BVC for such applications is always better than that of change coding and ROI coding.
19.	Khursheed, Khursheed, et al. (författare) Binary video codec for data reduction in wireless visual sensor networks 2013 Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE - International Society for Optical Engineering. - 9780819494290 ; , s. Art. no. 86560L- Konferensbidrag (refereegranskat)abstract Wireless Visual Sensor Networks (WVSN) is formed by deploying many Visual Sensor Nodes (VSNs) in the field. Typical applications of WVSN include environmental monitoring, health care, industrial process monitoring, stadium/airports monitoring for security reasons and many more. The energy budget in the outdoor applications of WVSN is limited to the batteries and the frequent replacement of batteries is usually not desirable. So the processing as well as the communication energy consumption of the VSN needs to be optimized in such a way that the network remains functional for longer duration. The images captured by VSN contain huge amount of data and require efficient computational resources for processing the images and wide communication bandwidth for the transmission of the results. Image processing algorithms must be designed and developed in such a way that they are computationally less complex and must provide high compression rate. For some applications of WVSN, the captured images can be segmented into bi-level images and hence bi-level image coding methods will efficiently reduce the information amount in these segmented images. But the compression rate of the bi-level image coding methods is limited by the underlined compression algorithm. Hence there is a need for designing other intelligent and efficient algorithms which are computationally less complex and provide better compression rate than that of bi-level image coding methods. Change coding is one such algorithm which is computationally less complex (require only exclusive OR operations) and provide better compression efficiency compared to image coding but it is effective for applications having slight changes between adjacent frames of the video. The detection and coding of the Region of Interest (ROIs) in the change frame efficiently reduce the information amount in the change frame. But, if the number of objects in the change frames is higher than a certain level then the compression efficiency of both the change coding and ROI coding becomes worse than that of image coding. This paper explores the compression efficiency of the Binary Video Codec (BVC) for the data reduction in WVSN. We proposed to implement all the three compression techniques i.e. image coding, change coding and ROI coding at the VSN and then select the smallest bit stream among the results of the three compression techniques. In this way the compression performance of the BVC will never become worse than that of image coding. We concluded that the compression efficiency of BVC is always better than that of change coding and is always better than or equal that of ROI coding and image coding. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
20.	Khursheed, Khursheed, 1983-, et al. (författare) Detecting and Coding Region of Interests in Bi-Level Images for Data Reduction in Wireless Visual Sensor Network 2012 Ingår i: Wireless and Mobile Computing, Networking and Communications (WiMob), 2012 IEEE 8th International Conference on. - : IEEE conference proceedings. - 9781467314299 ; , s. 705-712 Konferensbidrag (refereegranskat)abstract Wireless Visual Sensor Network (WVSN) is formed by deploying many Visual Sensor Nodes (VSNs) in the field. The VSNs acquire images of the area of interest in the field, perform some local processing on these images and transmit the results using an embedded wireless transceiver. The energy consumption on transmitting the results wirelessly is correlated with the information amount that is being transmitted. The images acquired by the VSNs contain huge amount of data due to many kinds of redundancies in the images. Suitable bi-level image compression standards can efficiently reduce the information amount in images and will thus be effective in reducing the communication energy consumption in the WVSN. But compression capability of the bi-level image compression standards is limited to the underline compression algorithm. Further data reduction can be achieved by detecting Region of Interest (ROI) in the bi-level images and then coding these ROIs using bi-level image compression method. We explored the compression performance of the lossless ROI detection and coding method for various kinds of changes such as different shapes, locations and number of objects in the continuous set of frames. The CCITT Group 4, JBIG2 and Gzip are used for coding the detected ROIs. We concluded that CCITT Group 4 is a better choice for coding the ROIs in the Bi-level images because of its comparatively good compression performance and less computational complexity. This paper is intended to be a resource for the researchers interested in reducing the amount of data in the bi-level images for energy constrained WVSNs.
21.	Khursheed, Khursheed, et al. (författare) Efficient Data Reduction Techniques for Remote Applications of a Wireless Visual Sensor Network 2013 Ingår i: International Journal of Advanced Robotic Systems. - : SAGE Publications. - 1729-8806 .- 1729-8814. ; 10, s. Art. no. 240- Tidskriftsartikel (refereegranskat)abstract A Wireless Visual Sensor Network (WVSN) is formed by deploying many Visual Sensor Nodes (VSNs) in the field. After acquiring an image of the area of interest, the VSN performs local processing on it and transmits the result using an embedded wireless transceiver. Wireless data transmission consumes a great deal of energy, where energy consumption is mainly dependent on the amount of information being transmitted. The image captured by the VSN contains a huge amount of data. For certain applications, segmentation can be performed on the captured images. The amount of information in the segmented images can be reduced by applying efficient bi-level image compression methods. In this way, the communication energy consumption of each of the VSNs can be reduced. However, the data reduction capability of bi-level image compression standards is fixed and is limited by the used compression algorithm. For applications attributing few changes in adjacent frames, change coding can be applied for further data reduction. Detecting and compressing only the Regions of Interest (ROIs) in the change frame is another possibility for further data reduction. In a communication system, where both the sender and the receiver know the employed compression standard, there is a possibility for further data reduction by not including the header information in the compressed bit stream of the sender. This paper summarizes different information reduction techniques such as image coding, change coding and ROI coding. The main contribution is the investigation of the combined effect of all these coding methods and their application to a few representative real life applications. This paper is intended to be a resource for researchers interested in techniques for information reduction in energy constrained embedded applications.
22.	Khursheed, Khursheed, 1983-, et al. (författare) Exploration of Local and Central Processing for a Wireless Camera Based Sensor Node 2010 Ingår i: International Conference on Signals and Electronic Systems, ICSES'10 - Conference Proceeding 2010, Article number 5595231. - : IEEE conference proceedings. - 9788390474342 - 9781424453078 ; , s. 147-150 Konferensbidrag (refereegranskat)abstract Wireless vision sensor network is an emerging field which combines image sensor, on board computation and communication links. Compared to the traditional wireless sensor networks which operate on one dimensional data, wireless vision sensor networks operate on two dimensional data which requires both higher processing power and communication bandwidth. The research focus within the field of wireless vision sensor network has been based on two different assumptions involving either sending data to the central base station without local processing or conducting all processing locally at the sensor node and transmitting only the final results. In this paper we focus on determining an optimal point for intelligence partitioning between the sensor node and the central base station and by exploring compression methods. The lifetime of the visual sensor node is predicted by evaluating the energy consumption for different levels of intelligence partitioning at the sensor node. Our results show that sending compressed images after segmentation will result in a longer life for the sensor node.
23.	Khursheed, Khursheed, et al. (författare) Exploration of tasks partitioning between hardware software and locality for a wireless camera based vision sensor node 2011 Ingår i: Proceedings - 6th International Symposium on Parallel Computing in Electrical Engineering, PARELEC 2011. - : IEEE conference proceedings. - 9780769543970 ; , s. 127-132 Konferensbidrag (refereegranskat)abstract In this paper we have explored different possibilities for partitioning the tasks between hardware, software and locality for the implementation of the vision sensor node, used in wireless vision sensor network. Wireless vision sensor network is an emerging field which combines image sensor, on board computation and communication links. Compared to the traditional wireless sensor networks which operate on one dimensional data, wireless vision sensor networks operate on two dimensional data which requires higher processing power and communication bandwidth. The research focus within the field of wireless vision sensor networks have been on two different assumptions involving either sending raw data to the central base station without local processing or conducting all processing locally at the sensor node and transmitting only the final results. Our research work focus on determining an optimal point of hardware/software partitioning as well as partitioning between local and central processing, based on minimum energy consumption for vision processing operation. The lifetime of the vision sensor node is predicted by evaluating the energy requirement of the embedded platform with a combination of FPGA and micro controller for the implementation of the vision sensor node. Our results show that sending compressed images after pixel based tasks will result in a longer battery life time with reasonable hardware cost for the vision sensor node. Â© 2011 IEEE.
24.	Khursheed, Khursheed (författare) Investigation of intelligence partitioning and data reduction in wireless visual sensor network 2013 Doktorsavhandling (övrigt vetenskapligt/konstnärligt)
25.	Khursheed, Khursheed (författare) Investigation of intelligence partitioning in wireless visual sensor networks 2011 Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract The wireless visual sensor network is an emerging field which is formed by deploying many visual sensor nodes in the field and in which each individual visual sensor node contains an image sensor, on board processor, memory and wireless transceiver. In comparison to the traditional wireless sensor networks, which operate on one dimensional data, the wireless visual sensor networks operate on two dimensional data which requires higher processing power and communication bandwidth. Research focus within the field of wireless visual sensor networks has been on two different extremes, involving either sending raw data to the central base station without local processing or conducting all processing locally at the visual sensor node and transmitting only the final results.This research work focuses on determining an optimal point of hardware/software partitioning at the visual sensor node as well as partitioning tasks between local and central processing, based on the minimum energy consumption for the vision processing tasks. Different possibilities in relation to partitioning the vision processing tasks between hardware, software and locality for the implementation of the visual sensor node, used in wireless visual sensor networks have been explored. The effect of packets relaying and node density on the energy consumption and implementation of the individual wireless visual sensor node, when used in a multi-hop wireless visual sensor networks have also been explored.The lifetime of the visual sensor node is predicted by evaluating the energy requirement of the embedded platform with a combination of the Field Programmable Gate Arrays (FPGA) and the micro-controller for the implementation of the visual sensor node and, in addition, taking into account the amount of energy required for receiving/forwarding the packets of other nodes in the multi-hop network.Advancements in FPGAs have been the motivation behind their choice as the vision processing platform for implementing visual sensor node. This choice is based on the reduced time-to-market, low Non-Recurring Engineering (NRE) cost and programmability as compared to ASICs. The other part of the architecture of the visual sensor node is the SENTIO32 platform, which is used for vision processing in the software implementation of the visual sensor node and for communicating the results to the central base station in the hardware implementation (using the RF transceiver embedded in SENTIO32).
26.	Khursheed, Khursheed, et al. (författare) Performance analysis of bi-level image compression methods for machine vision embedded applications Annan publikation (övrigt vetenskapligt/konstnärligt)
27.	Khursheed, Khursheed, 1983-, et al. (författare) Selection of bi-level image compression method for reduction of communication energy in wireless visual sensor networks 2012 Ingår i: SPIE. - : SPIE. - 9780819491299 Konferensbidrag (refereegranskat)abstract Wireless Visual Sensor Network (WVSN) is an emerging field which combines image sensor, on board computation unit, communication component and energy source. Compared to the traditional wireless sensor network, which operates on one dimensional data, such as temperature, pressure values etc., WVSN operates on two dimensional data (images) which requires higher processing power and communication bandwidth. Normally, WVSNs are deployed in areas where installation of wired solutions is not feasible. The energy budget in these networks is limited to the batteries, because of the wireless nature of the application. Due to the limited availability of energy, the processing at Visual Sensor Nodes (VSN) and communication from VSN to server should consume as low energy as possible. Transmission of raw images wirelessly consumes a lot of energy and requires higher communication bandwidth. Data compression methods reduce data efficiently and hence will be effective in reducing communication cost in WVSN. In this paper, we have compared the compression efficiency and complexity of six well known bi-level image compression methods. The focus is to determine the compression algorithms which can efficiently compress bi-level images and their computational complexity is suitable for computational platform used in WVSNs. These results can be used as a road map for selection of compression methods for different sets of constraints in WVSN.
28.	Khursheed, Khursheed, et al. (författare) The effect of packets relaying on the implementation issues of the visual sensor node 2013 Ingår i: Electronics and Electrical Engineering. - : Kaunas University of Technology (KTU). - 1392-1215 .- 2029-5731. ; 19:10, s. 155-161 Tidskriftsartikel (refereegranskat)abstract Wireless Visual Sensor Networks (WVSNs) are used for the monitoring of large and inaccessible areas. WVSNs are feasible today due to the advancement in many fields of electronics such as CMOS cameras, low power computing platforms, distributed computing and radio transceivers. The energy budget in a WVSN is limited because of the wireless nature of the applications and the small physical size of the Visual Sensor Node (VSN). The WVSN covers a large area where every node cannot transmit its results directly to the server. Receiving and forwarding other node's packets consumes a large portion of the energy budget of the VSNs. This paper explores the effect of packets relaying in a multihop WVSN on the implementation issues of the VSN. It also explores the effect of node density in the multihop WVSN on the energy consumption, which in turn, has an impact on the lifetime of the VSN. Results show that the network topology does not affect the software implementation of the VSN because of the relatively high execution time of the image processing tasks on the microcontroller. For hardware implementation, network topology and node density does affect the architecture of the VSN due to the fact that communication energy consumption is dominant (because of the low execution time on FPGAs).
29.	Aurangzeb, Khursheed, et al. (författare) Analysis of Binary Image Coding Methods for Outdoor Applications of Wireless Vision sensor Networks 2018 Ingår i: IEEE Access. - 2169-3536. ; 6, s. 16932-16941 Tidskriftsartikel (refereegranskat)abstract The processing of images at the vision sensor nodes (VSN) requires a high computation power and their transmission requires a large communication bandwidth. The energy budget is limited in outdoor applications of wireless vision sensor networks (WVSN). This means that both the processing of images at the VSN and the communication to server must be energy efficient. The wireless communication of uncompressed data consumes huge amounts of energy. Data compression methods are efficient in reducing data in images and can be used for the reduction in transmission energy. We have evaluated seven binary image coding techniques. Our evaluation is based on the processing complexity and energy consumption of the compression methods on the embedded platforms. The focus is to come up with a binary image coding method, which has good compression efficiency and short processing time. An image coding method with such attributes will result in reduced total energy requirement of the node. We have used both statistically generated images and real captured images, in our experiments. Based on our results, we conclude that International Telegraph and Telephone Consultative Committee Group 4, gzip_pack and JPEG-LS are suitable coding methods for the outdoor applications of WVSNs.
30.	Aurangzeb, Khursheed, et al. (författare) Data Reduction Using Change Coding for Remote Applications of wireless Visual Sensor Networks 2018 Ingår i: IEEE Access. - : IEEE. - 2169-3536. ; 6, s. 37738-37747 Tidskriftsartikel (refereegranskat)abstract The data reduction capability of image compression schemes is limited by the underlying compression technique. For applications with minor changes between consecutive frames, change coding can be used to further reduce the data. We explored the efficiency of change coding for data reduction in a wireless visual sensor network (WVSN). This paper presents an analysis of the compression efficiency of change coding for a variety of changes, such as different shapes, sizes, and locations of white objects in adjacent sets of frames. Compressing change frame provides a better performance compared with compressing the original frames for up to 95% changes in the number of objects in adjacent frames. Due to illumination noise, the size of the objects increases at its boundaries, which negatively affects the performance of change coding. We experimentally proved that the negative impact of illumination noise could be reduced by applying morphology on the change frame. Communication energy consumption of the VSN is dependent on the data that are transmitted to the server. Our results show that the communication energy consumption of the VSN can be reduced by 27%, 29%, and 46% by applying change coding in combination with JBIG2, Group4, and Gzip_pack, respectively. The findings presented in this paper will aid researchers in enhancing the compression potential of image coding schemes in the energy-constrained applications of WVSNs.
31.	Khursheed, A., et al. (författare) Future liasing of the lockdown during COVID-19 pandemic : The dawn is expected at hand from the darkest hour 2020 Ingår i: Groundwater for Sustainable Development. - : Elsevier B.V.. - 2352-801X. ; 11 Tidskriftsartikel (refereegranskat)abstract The lockdown during COVID-19 pandemic has converted the world into new experimental laboratories, which may reveal temporal or spatial comparative analysis data. However, some startling information is gathered in terms of reduced premature mortality cases associated with air and water quality improvement, enhanced e-learning on a broader platform, work from home, and successful e-health. The decline in vehicular density on roads and congestion leads to reduced energy consumption and associated greenhouse gases (GHG) and other pollutants emission. The lockdown has also been identified as a possible emergency measure to combat severe air pollution episodes. Similarly, industrial pollution has been recognized as one of the primary causes of water resource pollution and would, therefore, bring change in policy vis-à-vis groundwater pollution control. Our findings suggest that the results of successful e-learning and work from home would be a permanent shift from conventional modes in the near future due to a drastic reduction in socio-economic cost. Our critical analysis also highlights that with such temporary lockdown measures acute/chronic ill-effects of anthropogenic perturbations on planet earth can be effectively estimated through sociocultural, socioeconomical and socio-political/sociotechnological nexus.
32.	Kumar, M., et al. (författare) A chronicle of SARS-CoV-2 : Seasonality, environmental fate, transport, inactivation, and antiviral drug resistance 2021 Ingår i: Journal of Hazardous Materials. - : Elsevier B.V.. - 0304-3894 .- 1873-3336. ; 405 Tidskriftsartikel (refereegranskat)abstract In this review, we present the environmental perspectives of the viruses and antiviral drugs related to SARS-CoV-2. The present review paper discusses occurrence, fate, transport, susceptibility, and inactivation mechanisms of viruses in the environment as well as environmental occurrence and fate of antiviral drugs, and prospects (prevalence and occurrence) of antiviral drug resistance (both antiviral drug resistant viruses and antiviral resistance in the human). During winter, the number of viral disease cases and environmental occurrence of antiviral drug surge due to various biotic and abiotic factors such as transmission pathways, human behaviour, susceptibility, and immunity as well as cold climatic conditions. Adsorption and persistence critically determine the fate and transport of viruses in the environment. Inactivation and disinfection of virus include UV, alcohol, and other chemical-base methods but the susceptibility of virus against these methods varies. Wastewater treatment plants (WWTPs) are major reserviors of antiviral drugs and their metabolites and transformation products. Ecotoxicity of antiviral drug residues against aquatic organisms have been reported, however more threatening is the development of antiviral resistance, both in humans and in wild animal reservoirs. In particular, emergence of antiviral drug-resistant viruses via exposure of wild animals to high loads of antiviral residues during the current pandemic needs further evaluation.

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