Journal articles: 'Smart camera embedded system'

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Zarezadeh, Ali Akbar, and Christophe Bobda. "Hardware Middleware for Person Tracking on Embedded Distributed Smart Cameras." International Journal of Reconfigurable Computing 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/615824.

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Tracking individuals is a prominent application in such domains like surveillance or smart environments. This paper provides a development of a multiple camera setup with jointed view that observes moving persons in a site. It focuses on a geometry-based approach to establish correspondence among different views. The expensive computational parts of the tracker are hardware accelerated via a novel system-on-chip (SoC) design. In conjunction with this vision application, a hardware object request broker (ORB) middleware is presented as the underlying communication system. The hardware ORB provides a hardware/software architecture to achieve real-time intercommunication among multiple smart cameras. Via a probing mechanism, a performance analysis is performed to measure network latencies, that is, time traversing the TCP/IP stack, in both software and hardware ORB approaches on the same smart camera platform. The empirical results show that using the proposed hardware ORB as client and server in separate smart camera nodes will considerably reduce the network latency up to 100 times compared to the software ORB.

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Choi, Won Hyuck, and Min Seok Jie. "Development of Smart Remote Local Information Embedded System Using Global Positioning System." Applied Mechanics and Materials 681 (October 2014): 51–56. http://dx.doi.org/10.4028/www.scientific.net/amm.681.51.

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In case of existing localization system, it usually depends on video information by camera. Therefore, the camera has to be operated 24 hours a day. For the special region of interest, position recognition is available, however, for the most cases, once the camera is out of observed extent, the position recognition is not available. In order to back up these disadvantages, the Wireless Sensor Network, by using GPS and various sensors, can detect and monitoring the data up to the area which the image information cannot detect. For this, the thesis suggests the efficient monitoring system using GPS and human body detecting sensor.

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Singh, Sanjay, Srinivasa Murali Dunga, AS Mandal, Chandra Shekhar, and Santanu Chaudhury. "FPGA Based Embedded Implementation of Video Summary Generation Scheme in Smart Camera." Advanced Materials Research 403-408 (November 2011): 516–21. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.516.

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In any remote surveillance scenario, smart cameras have to take intelligent decisions to generate summary frames to minimize communication and processing overhead. Video summary generation, in the context of smart camera, is the process of merging the information from multiple frames. A summary generation scheme based on clustering based change detection algorithm has been implemented in our smart camera system for generating frames to deliver requisite information. In this paper we propose an embedded platform based framework for implementing summary generation scheme using HW-SW Co-Design based methodology. The complete system is implemented on Xilinx XUP Virtex-II Pro FPGA board. The overall algorithm is running on PowerPC405 and some of the blocks which are computationally intensive and more frequently called are implemented in hardware using VHDL. The system is designed using Xilinx Embedded Design Kit (EDK).

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Hsu, Ting-Yu, and Xiang-Ju Kuo. "A Stand-Alone Smart Camera System for Online Post-Earthquake Building Safety Assessment." Sensors 20, no. 12 (June 15, 2020): 3374. http://dx.doi.org/10.3390/s20123374.

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Computer vision-based approaches are very useful for dynamic displacement measurement, damage detection, and structural health monitoring. However, for the application using a large number of existing cameras in buildings, the computational cost of videos from dozens of cameras using a centralized computer becomes a huge burden. Moreover, when a manual process is required for processing the videos, prompt safety assessment of tens of thousands of buildings after a catastrophic earthquake striking a megacity becomes very challenging. Therefore, a decentralized and fully automatic computer vision-based approach for prompt building safety assessment and decision-making is desired for practical applications. In this study, a prototype of a novel stand-alone smart camera system for measuring interstory drifts was developed. The proposed system is composed of a single camera, a single-board computer, and two accelerometers with a microcontroller unit. The system is capable of compensating for rotational effects of the camera during earthquake excitations. Furthermore, by fusing the camera-based interstory drifts with the accelerometer-based ones, the interstory drifts can be measured accurately even when residual interstory drifts exist. Algorithms used to compensate for the camera’s rotational effects, algorithms used to track the movement of three targets within three regions of interest, artificial neural networks used to convert the interstory drifts to engineering units, and some necessary signal processing algorithms, including interpolation, cross-correlation, and filtering algorithms, were embedded in the smart camera system. As a result, online processing of the video data and acceleration data using decentralized computational resources is achieved in each individual smart camera system to obtain interstory drifts. Using the maximum interstory drifts measured during an earthquake, the safety of a building can be assessed right after the earthquake excitation. We validated the feasibility of the prototype of the proposed smart camera system through the use of large-scale shaking table tests of a steel building. The results show that the proposed smart camera system had very promising results in terms of assessing the safety of steel building specimens after earthquake excitations.

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Saidi, Youcef, Larbi Boumediene, Mohammed Amine Benmahdjoub, and Abdelkader Mezouar. "Smart embarked electrical network based on embedded system and monitoring camera." International Journal of Computational Science and Engineering 22, no. 1 (2020): 15. http://dx.doi.org/10.1504/ijcse.2020.10029208.

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Benmahdjoub, Mohammed Amine, Abdelkader Mezouar, Larbi Boumediene, and Youcef Saidi. "Smart embarked electrical network based on embedded system and monitoring camera." International Journal of Computational Science and Engineering 22, no. 1 (2020): 15. http://dx.doi.org/10.1504/ijcse.2020.107236.

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Mosqueron, Romuald, Julien Dubois, Marco Mattavelli, and David Mauvilet. "Smart Camera Based on Embedded HW/SW Coprocessor." EURASIP Journal on Embedded Systems 2008, no. 1 (2008): 597872. http://dx.doi.org/10.1155/2008/597872.

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Cob-Parro, Antonio Carlos, Cristina Losada-Gutiérrez, Marta Marrón-Romera, Alfredo Gardel-Vicente, and Ignacio Bravo-Muñoz. "Smart Video Surveillance System Based on Edge Computing." Sensors 21, no. 9 (April 23, 2021): 2958. http://dx.doi.org/10.3390/s21092958.

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New processing methods based on artificial intelligence (AI) and deep learning are replacing traditional computer vision algorithms. The more advanced systems can process huge amounts of data in large computing facilities. In contrast, this paper presents a smart video surveillance system executing AI algorithms in low power consumption embedded devices. The computer vision algorithm, typical for surveillance applications, aims to detect, count and track people’s movements in the area. This application requires a distributed smart camera system. The proposed AI application allows detecting people in the surveillance area using a MobileNet-SSD architecture. In addition, using a robust Kalman filter bank, the algorithm can keep track of people in the video also providing people counting information. The detection results are excellent considering the constraints imposed on the process. The selected architecture for the edge node is based on a UpSquared2 device that includes a vision processor unit (VPU) capable of accelerating the AI CNN inference. The results section provides information about the image processing time when multiple video cameras are connected to the same edge node, people detection precision and recall curves, and the energy consumption of the system. The discussion of results shows the usefulness of deploying this smart camera node throughout a distributed surveillance system.

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Sabri, Naseer, M. S. Salim, S. Fouad, S. Alwee Aljunid, F. T. AL-Dhief, and C. B. M. Rashidi. "Design and Implementation of an Embedded Smart Intruder Surveillance System." MATEC Web of Conferences 150 (2018): 06019. http://dx.doi.org/10.1051/matecconf/201815006019.

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Remote and scattered valuable and sensitive locations such as labs and offices inside university campus need efficient monitoring and warning system. As well as scattered area and belonging. This research presents a Real-Time intruder Surveillance System based on a single board computer (SBC). Thus the design and development of a cost effective surveillance management system based SBC that can be deployed efficiently in remote and scattered locations such as universities belonging. The fusion of embedded Python codes with SBC that attached to cameras, Long distance sensors, alerting circuitry and wireless module presents a novel integration based effective cost solution and enhances SBC of much flexibility of improvement and development for pervasive remote locations. The system proves the high integrity of smooth working with web application, it’s cost effective and thus can be deployed as many of units to seize and concisely covered remote and scattered area as well as university belonging and departments. The system can be administrated by a remote user sparsely or geographically away from any networked workstation. The proposed solution offers efficient stand alone, flexibility to upgrade and cheap development and installation as well as cost effective ubiquitous surveillance solution. In conclusion, the system acceptable boundaries of successful intruder recognition and warning alert are computed between 1m and 3m distance of intruder from system camera. Recognition rate of 95% and 83% are achieved and the successful warning alert were in the range of 86-97%.

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Zhang, Peng Ju, Gai Zhi Guo, and Zong Zuo Yu. "Application of Wireless Sensor Network in Embedded Smart Home System." Applied Mechanics and Materials 738-739 (March 2015): 74–78. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.74.

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This paper presents an Embedded Smart Home system solution using wireless sensor network (WSN). The Smart Home system can be sectioned into four parts: wireless sensor network, embedded smart control centre, Server and Client. The major technical of the wireless sensor network is ZigBee. The wireless sensor network includes coordinator node and Sensor node. It is developed based on the Z-Stack protocol stack and the wireless chip CC2530. It is mainly responsible for collecting the environmental parameter of the house and controlling the electrical equipment in the house. It can also support the RFID access control and camera monitor. The control centre communicates with the wireless sensor network by the serial port. It communicates with Server by the TCP socket and transmits data to each client, or communicates with the client by using the wireless communication module directly. Partial hardware electric diagram and software flowchart were provided. Field using indicates that this system is economical and flexible.

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Ma, Zheng, and Guan Bo Wang. "Research on Camera-Oriented Smart Car and Intelligent Control." Applied Mechanics and Materials 260-261 (December 2012): 342–47. http://dx.doi.org/10.4028/www.scientific.net/amm.260-261.342.

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This paper designs a camera-oriented smart car along with specialized intelligent control algorithms. MC9S12XS128 is chosen as the central processing unit and a CCD sensor along with peripheral circuit is designed as the camera module. The proposed system integrates technologies of intelligent control, Micro-Electro-Mechanism System (MEMS), System on Chip (SOC), wireless communication and low power consumption embedded technology, realizing autonomous navigation while tracking the path. In the paper, the extraction of path information is streamlined, where dynamic threshold method is used for image binarization and path optimization is done with least square method. Control algorithms are highlighted, where servo control incorporates least squares method creatively and the DC motor control, forming a closed-loop system with a rotatory encoder, adopts incremental PID control algorithm.

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Zhang, Peng Ju, Gai Zhi Guo, and Zong Zuo Yu. "Design of Embedded Smart Home System Based on Internet of Things." Applied Mechanics and Materials 738-739 (March 2015): 247–50. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.247.

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This paper presents an Embedded Smart Home system solution using the Internet of things. The Smart Home system can be sectioned into four parts: wireless sensor network, embedded smart gateway, Server and Client. The major technical of the wireless sensor network is ZigBee. The wireless sensor network is developed based on the Z-Stack protocol stack and the wireless chip CC2530. Its main work is to sensor the environmental parameter of the house and the automation control of the electrical equipment in the house. It can also support the RFID access control and camera monitor. ARM microprocessor is the core of the Embedded Smart Home control system. It adopts the embedded Linux technology, the development platform is Qt. The gateway communicates with the wireless sensor network by the serial port. It communicates with Server by the TCP socket and transmits to each client, or communicates with the client by using the wireless communication module directly. It also provides the user interface for sensor data check and real time control equipment. The server plays a role of bridge. It is mainly responsible for the communication and big data processing between the client and the control center. Partial hardware electric diagram and software flowchart were provided. Field using indicates that this system is economical and flexible.

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Sun, Qi Yuan, Lei Ma, and Zuo Liang Cao. "Optimization and Realization of Target Tracking Algorithm Based on Embedded System." Advanced Materials Research 468-471 (February 2012): 2352–56. http://dx.doi.org/10.4028/www.scientific.net/amr.468-471.2352.

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Target tracking algorithm is used widely in many fields, such as robot vision system, intelligent surveillance and medicine, but computational complexity and lack of dedicated embedded system for real-time processing have affected its application. This paper presents a method that combines embedded system, smart camera and mobile robot for detecting and tracking the moving targets. On the basis of particle filter algorithm, mean shift embedded particle filter algorithm is proposed and implemented on embedded platform with ARM+DSP dual core framework. At last, the whole system is optimized to improve the real-time property. The proposed method has a very powerful data processing ability, which can offer a high reliability for the navigation of a mobile robot.

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Dessai, Sanket, Deepa Kannan, and Shiva Prasa Yadav. "Implementation of video surveillance system using embedded Blackfin processor." International Journal of Reconfigurable and Embedded Systems (IJRES) 10, no. 2 (July 1, 2021): 115. http://dx.doi.org/10.11591/ijres.v10.i2.pp115-122.

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The video surveillance is critical system to track the people at the various places and to track and monitor the nuciencess bound to be happened. On the other side several studies have proved and showed the hit and miss nature of human intervention to spot change in a surrounding environment which increasing the designer challenges for the development of video surveillance system with the help of embedded processor. The designer faces a greater challenge to apply the principle of embedded systems and develop the system smart features with low power and cost for the required applications of VSS. System requirement specification (SRS), Hardware design document (HDD), Software design document and test procedure has been arrived and developed to achieve VSS system. Blackfin processor has high end video engines and is more suitable for development of video surveillance system (VSS). The VSS is designed and developed using ADSP BF533 Ez-kit lite board. Peripheral like parallel peripheral interface (PPI) is used to interface between camera and processor. Also, it is used for interfacing processor and TV. The master-slave communication is established between two Blackfin processors through SPORT to transfer the captured frame from camera to display on TV. Power management is also implemented to save the power of the system.

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Kryjak, Tomasz, Mateusz Komorkiewicz, and Marek Gorgon. "Real-time hardware–software embedded vision system for ITS smart camera implemented in Zynq SoC." Journal of Real-Time Image Processing 15, no. 1 (May 4, 2016): 123–59. http://dx.doi.org/10.1007/s11554-016-0588-9.

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Piras, M., N. Grasso, and A. Abdul Jabbar. "UAV PHOTOGRAMMETRIC SOLUTION USING A RASPBERRY PI CAMERA MODULE AND SMART DEVICES: TEST AND RESULTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W6 (August 24, 2017): 289–96. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w6-289-2017.

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Nowadays, smart technologies are an important part of our action and life, both in indoor and outdoor environment. There are several smart devices very friendly to be setting, where they can be integrated and embedded with other sensors, having a very low cost. Raspberry allows to install an internal camera called Raspberry Pi Camera Module, both in RGB band and NIR band. The advantage of this system is the limited cost (<&thinsp;60 euro), their light weight and their simplicity to be used and embedded. This paper will describe a research where a Raspberry Pi with the Camera Module was installed onto a UAV hexacopter based on arducopter system, with purpose to collect pictures for photogrammetry issue. Firstly, the system was tested with aim to verify the performance of RPi camera in terms of frame per second/resolution and the power requirement. Moreover, a GNSS receiver Ublox M8T was installed and connected to the Raspberry platform in order to collect real time position and the raw data, for data processing and to define the time reference. IMU was also tested to see the impact of UAV rotors noise on different sensors like accelerometer, Gyroscope and Magnetometer. A comparison of the achieved results (accuracy) on some check points of the point clouds obtained by the camera will be reported as well in order to analyse in deeper the main discrepancy on the generated point cloud and the potentiality of these proposed approach. In this contribute, the assembling of the system is described, in particular the dataset acquired and the results carried out will be analysed.

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Zeng, Gao Rong, and Gang Liu. "Design and Implementation of the Object Video Surveillance Base on Smart Phone Terminal." Advanced Materials Research 905 (April 2014): 556–59. http://dx.doi.org/10.4028/www.scientific.net/amr.905.556.

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Video surveillance systems play an important role in safety monitoring and intelligent management of the important object. Compared to the traditional multimedia monitoring system,the low-cost and low-power embedded mobile video monitoring system will enter soon the marketplace with the promise of flexibility, quick deployment and providing accurate and real-time visual data. This paper proposed a monitoring scheme based on android smart phone terminal, ARM processor, a wireless router and camera, which makes it possible to monitor the target site anywhere and anytime under the coverage of wireless network and enhances the flexibility of surveillance system greatly.

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KHALIL, MOHAMMED S., FAJRI KURNIAWAN, and KASHIF SALEEM. "AUTHENTICATION OF FINGERPRINT BIOMETRICS ACQUIRED USING A CELLPHONE CAMERA: A REVIEW." International Journal of Wavelets, Multiresolution and Information Processing 11, no. 05 (September 2013): 1350033. http://dx.doi.org/10.1142/s0219691313500331.

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Over the past decade, there have been dramatic increases in the usage of mobile phones in the world. Currently available smart mobile phones are capable of storing enormous amounts of personal information/data. The smart mobile phone is also capable of connecting to other devices, with the help of different applications. Consequently, with these connections comes the requirement of security to protect personal information. Nowadays, in many applications, a biometric fingerprint recognition system has been embedded as a primary security measure. To enable a biometric fingerprint recognition system in smart mobile phones, without any additional costs, a built-in high performance camera can be utilized. The camera can capture the fingerprint image and generate biometric traits that qualify the biometric fingerprint authentication approach. However, the images acquired by a mobile phone are entirely different from the images obtained by dedicated fingerprint sensors. In this paper, we present the current trend in biometric fingerprint authentication techniques using mobile phones and explore some of the future possibilities in this field.

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Xia, Kun, Hongliang Fan, Jianguang Huang, Hanyu Wang, Junxue Ren, Qin Jian, and Dafang Wei. "An Intelligent Self-Service Vending System for Smart Retail." Sensors 21, no. 10 (May 20, 2021): 3560. http://dx.doi.org/10.3390/s21103560.

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The traditional weighing and selling process of non-barcode items requires manual service, which not only consumes manpower and material resources but is also more prone to errors or omissions of data. This paper proposes an intelligent self-service vending system embedded with a single camera to detect multiple products in real-time performance without any labels, and the system realizes the integration of weighing, identification, and online settlement in the process of non-barcode items. The system includes a self-service vending device and a multi-device data management platform. The flexible configuration of the structure gives the system the possibility of identifying fruits from multiple angles. The height of the system can be adjusted to provide self-service for people of different heights; then, deep learning skill is applied implementing product detection, and real-time multi-object detection technology is utilized in the image-based checkout system. In addition, on the multi-device data management platform, the information docking between embedded devices, WeChat applets, Alipay, and the database platform can be implemented. We conducted experiments to verify the accuracy of the measurement. The experimental results demonstrate that the correlation coefficient R2 between the measured value of the weight and the actual value is 0.99, and the accuracy of non-barcode item prediction is 93.73%. In Yangpu District, Shanghai, a comprehensive application scenario experiment was also conducted, proving that our system can effectively deal with the challenges of various sales situations.

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Dworak, Volker, Joern Selbeck, Karl-Heinz Dammer, Matthias Hoffmann, Ali Zarezadeh, and Christophe Bobda. "Strategy for the Development of a Smart NDVI Camera System for Outdoor Plant Detection and Agricultural Embedded Systems." Sensors 13, no. 2 (January 24, 2013): 1523–38. http://dx.doi.org/10.3390/s130201523.

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Pelissier, Frantz, Hanen Chenini, François Berry, Alexis Landrault, and Jean-Pierre Derutin. "Embedded multi-processor system-on-programmable chip for smart camera pose estimation using nonlinear optimization methods." Journal of Real-Time Image Processing 12, no. 4 (September 30, 2014): 663–79. http://dx.doi.org/10.1007/s11554-014-0454-6.

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Guo, Zhonghua, Meng Zhang, Dah-Jye Lee, and Taylor Simons. "Smart Camera for Quality Inspection and Grading of Food Products." Electronics 9, no. 3 (March 19, 2020): 505. http://dx.doi.org/10.3390/electronics9030505.

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Due to the increasing consumption of food products and demand for food quality and safety, most food processing facilities in the United States utilize machines to automate their processes, such as cleaning, inspection and grading, packing, storing, and shipping. Machine vision technology has been a proven solution for inspection and grading of food products since the late 1980s. The remaining challenges, especially for small to midsize facilities, include the system and operating costs, demand for high-skilled workers for complicated configuration and operation and, in some cases, unsatisfactory results. This paper focuses on the development of an embedded solution with learning capability to alleviate these challenges. Three simple application cases are included to demonstrate the operation of this unique solution. Two datasets of more challenging cases were created to analyze and demonstrate the performance of our visual inspection algorithm. One dataset includes infrared images of Medjool dates of four levels of skin delamination for surface quality grading. The other one consists of grayscale images of oysters with varying shape for shape quality evaluation. Our algorithm achieved a grading accuracy of 95.0% on the date dataset and 98.6% on the oyster dataset, both easily surpassed manual grading, which constantly faces the challenges of human fatigue or other distractions. Details of the design and functions of our smart camera and our simple visual inspection algorithm are discussed in this paper.

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Chang, Ching-Yuan, En-Chieh Chang, and Chi-Wen Huang. "In Situ Diagnosis of Industrial Motors by Using Vision-Based Smart Sensing Technology." Sensors 19, no. 24 (December 4, 2019): 5340. http://dx.doi.org/10.3390/s19245340.

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This study uses machine vision, feature extraction, and support vector machine (SVM) to compose a vibration monitoring system (VMS) for an in situ evaluation of the performance of industrial motors. The vision-based system respectively offers a spatial and temporal resolution of 1.4 µm and 16.6 ms after the image calibration and the benchmark of a laser displacement sensor (LDS). The embedded program of machine vision has used zero-mean normalized correlation (ZNCC) and peak finding (PF) for tracking the registered characteristics on the object surface. The calibrated VMS provides time–displacement curves related to both horizontal and vertical directions, promising remote inspections of selected points without attaching additional markers or sensors. The experimental setup of the VMS is cost-effective and uncomplicated, supporting universal combinations between the imaging system and computational devices. The procedures of the proposed scheme are (1) setting up a digital camera, (2) calibrating the imaging system, (3) retrieving the data of image streaming, (4) executing the ZNCC criteria, and providing the time–displacement results of selected points. The experiment setup of the proposed VMS is straightforward and can cooperate with surveillances in industrial environments. The embedded program upgrades the functionality of the camera system from the events monitoring to remote measurement without the additional cost of attaching sensors on motors or targets. Edge nodes equipped with the image-tracking program serve as the physical layer and upload the extracted features to a cloud server via the wireless sensor network (WSN). The VMS can provide customized services under the architecture of the cyber–physical system (CPS), and this research offers an early warning alarm of the mechanical system before unexpected downtime. Based on the smart sensing technology, the in situ diagnosis of industrial motors given from the VMS enables preventative maintenance and contributes to the precision measurement of intelligent automation.

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Vinoth Kumar, M., J. Gobinath, and M. Sangeetha. "Real-Time Distributed Wireless Sensor Network for Monitoring Smart Agricultural Environment." Applied Mechanics and Materials 573 (June 2014): 388–93. http://dx.doi.org/10.4028/www.scientific.net/amm.573.388.

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In India 75% land is occupied for agriculture so some recent survey shows 85% of fresh water resources is utilized in every seasonal period. We can overcome this water consumption through the help of embedded wireless sensor equipments. In this paper we projected a new idea, the system have distributed wireless network to monitor a soil-moisture. Temperature sensors are placed in the root zone of the plants and all these sensors are self power sourced through batteries with an inbuilt rechargeable photovoltaic cell to charge them. Using GPRS system it can be monitored accurately from outsource, and another main action to be achieved in this agriculture environment. The overall environment will be monitored through a digital camera to avoid the infection in plants and also fertilizing them in a correct time. The automated system actions are analyzed and monitored in the server or data storage room.

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Kraft, Marek, Przemysław Aszkowski, Dominik Pieczyński, and Michał Fularz. "Low-Cost Thermal Camera-Based Counting Occupancy Meter Facilitating Energy Saving in Smart Buildings." Energies 14, no. 15 (July 27, 2021): 4542. http://dx.doi.org/10.3390/en14154542.

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Using passive infrared sensors is a well-established technique of presence monitoring. While it can significantly reduce energy consumption, more savings can be made when utilising more modern sensor solutions coupled with machine learning algorithms. This paper proposes an improved method of presence monitoring, which can accurately derive the number of people in the area supervised with a low-cost and low-energy thermal imaging sensor. The method utilises U-Net-like convolutional neural network architecture and has a low parameter count, and therefore can be used in embedded scenarios. Instead of providing simple, binary information, it learns to estimate the occupancy density function with the person count and approximate location, allowing the system to become considerably more flexible. The tests show that the method compares favourably to the state of the art solutions, achieving significantly better results.

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Bahaghighat, Mahdi, and Seyed Motamedi. "Vision inspection and monitoring of wind turbine farms in emerging smart grids." Facta universitatis - series: Electronics and Energetics 31, no. 2 (2018): 287–301. http://dx.doi.org/10.2298/fuee1802287b.

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Todays, Smart Grids as the goal of next generation power grid system span wide and new aspects of power generation from distributed and bulk power generators to the end-user utilities. There are many advantages to develop these complex and multilayer system of systems such as increasing agility, reliability, efficiency, privacy, security for both Energy and ICT sections in smart grid architecture. In emerging smart grids, the communication infrastructures play main role in grid development and as a result multimedia applications are more practical for the future power systems. In this work, we introduce our method for monitoring and inspection of Wind Turbine (WT) farms in smart grids. In our proposed system, a thermal vision camera is embedded on a wireless sensor node for each WT to capture appropriate images and send video streams to the coordinator. It gets video frames to perform machine Vision Inspection (VI) and monitoring purposes. In our constructed model, turbine blade velocity estimation is targeted by detecting two important landmarks in the image that are named hub and blade. By tracking the blade in the consecutive frames and based on proposed scoring function, we can estimate the velocity of the turbine blade. Obtained results clearly indicate that accurate hub and blade positions extraction lead to error free estimation of turbine blade velocity.

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Lee, In Jung. "The SoC Design for Facial Expression Recognition with Adaptive Speedy Algorithm in Order to Camera System." Applied Mechanics and Materials 378 (August 2013): 662–68. http://dx.doi.org/10.4028/www.scientific.net/amm.378.662.

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Smart and emerging technologies require fast processing hardware and software fusion solutions. In this paper we propose SoC design for facial expression recognition with adaptive speedy algorithm. In this order a shape detection algorithm is implemented on conditional random fields. In this way the conditional random fields is calculated into speedy conditional random fields (SCRF). On this new fields shape detection algorithm become speedy. The detection algorithm is designed and implemented fully as hardware and the block architecture uses indexed register bank with 1 clock delay output and with minimum latency. The block fits in a Xilinx Vertex5 device requiring 45,110 LUTs and No camera data memory. Additionally S3C6410 embedded board with processing ARM-11 was attached to device to further operations. The pointing input device SoC supports the proposed facial expression recognition will be fabricated.

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Anitha, Raju, M. Nishitha, K. Akhila, K. Sai Anusha, and G. Srilekha. "IoTbased smart and flexible lightning in streets." International Journal of Engineering & Technology 7, no. 2.8 (March 19, 2018): 291. http://dx.doi.org/10.14419/ijet.v7i2.8.10426.

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The internet of Things (IOT) is always giving unprecedented answers for the customary issues looked by man.One of the real obstacles in city is we are spending huge expenses on street light. To control the street lights based on detection of sunlight by implemented with smart embedded system. The paper is mainly utilized for smart and climate adaptive lighting in street lights. The street lights are automatically ON during the evening time and automatically OFF during day time.The street light can be accessed to turn ON or OFF at anyplace and anytime through web.In addition to that On top of the street light we are placing camera to track the activities performed on the street and where the recordings are stored in a server. Furthermore a panic button is placed on the pole, If there is any emergency situations like harassment, robbery there is a panic button is available at the reachable height any person can press it if he is in danger. If people are unable to press the panic button, they should use voice recognition which is connected to panic button, when it recognises some commands like help, it automatically press the panic button. Whenever the panic button is pressed, the footages at that time recorded by the camera is sent straightforwardly to the cloud account. The near specific police headquarters can have access of the account by which they can see the incident’s spot. Every region's street lights are associated with the specific area's police headquarters and cloud account can be accessible by each of them. Here GSMTechnology is eliminated completely.Safety and energy consumptions can be ensured by this idea.

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Bahaghighat, Mahdi, Seyed Ahmad Motamedi, and Qin Xin. "Image Transmission over Cognitive Radio Networks for Smart Grid Applications." Applied Sciences 9, no. 24 (December 13, 2019): 5498. http://dx.doi.org/10.3390/app9245498.

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Today, Smart Grids (SGs), as the goal of the next-generation power grid system, span extremely wide aspects from power generation to end-user utilities. In smart grids, Energy and Information flows are mutually dependent and performance degradation of one side may have a high impact on the other side. In this work, we introduce our architecture for monitoring of Wind Turbine (WT) farms in smart grids. In our proposed system an industrial camera is embedded on a Wireless Cognitive Radio node for each WT to capture appropriate images and stream videos to the cognitive coordinator. Any packet loss in transmission between an embedded cognitive node and the coordinator can degrade peak signal-to-noise ratio (PSNR) of the received images. The image streaming is a delay sensitive transmission which should be done in harsh environments in SGs. To tackle these challenging issues, we introduce our efficient model, called JOPSS, for joint optimization of both packet size and Number of Spectrum Sensing Iterations (NSSI) during image transmission in time-restricted conditions. We define our proposed objective function as the quotient of the Overhead Time and the Effective Transmission Time (ETT). In addition, we introduce our methods based on the Minimum of Overhead Time Channel Selection (MOTS) for the efficient channel selection along with Dynamic Parameter Updating Procedure (DPUP) to benefit different strategies in Mandatory and Proactive Handoffs (MHO/PHO). The obtained results show that noticeable improvements in both PSNR and feature-similarity (FSIM) can be achieved on our models JOPSS and JOPSS-SAFE, respectively.

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Syukuryansyah, Ridho, Didik Setiyadi, and Syahbaniar Rofiah. "PENERAPAN RADIO FREQUENCY IDENTIFICATION DALAM MEMBANGUN SISTEM KEAMANAN DAN MONITORING SMART LOCK DOOR BERBASIS WEBSITE." Infotech: Journal of Technology Information 6, no. 2 (November 26, 2020): 83–90. http://dx.doi.org/10.37365/jti.v6i2.91.

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Technology in this modernization era helps many workers and human needs. Various fields have been encroached upon by technology and one cannot be released again, one of which is security systems. The need for increased security is based on human needs for a sense of comfort with the assets they have in a safe condition and can be monitored from anytime and anywhere. This research aims to build a security system using RFID and Arduino which can be monitored through the website. An early warning system for unknown objects is also embedded therein using a magnetic switch sensor on the door, buzzer to create sound frequencies that can attract the attention of the surrounding environment and the Arduino camera module to capture images of objects. The results of this research RFID can facilitate access in and out of the door and increase security compared to conventional keys. Only registered / known objects can access the room through the door. In and out activities are monitored through a website that can be accessed anytime and anywhere.

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Kraljević, Luka, Mladen Russo, Matija Pauković, and Matko Šarić. "A Dynamic Gesture Recognition Interface for Smart Home Control based on Croatian Sign Language." Applied Sciences 10, no. 7 (March 27, 2020): 2300. http://dx.doi.org/10.3390/app10072300.

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Deaf and hard-of-hearing people are facing many challenges in everyday life. Their communication is based on the use of a sign language, and the ability of the cultural/social environment to fully understand such a language defines whether or not it will be accessible for them. Technology is a key factor that has the potential to provide solutions to achieve a higher accessibility and therefore improve the quality of life of deaf and hard-of-hearing people. In this paper, we introduce a smart home automatization system specifically designed to provide real-time sign language recognition. The contribution of this paper implies several elements. Novel hierarchical architecture is presented, including resource-and-time-aware modules—a wake-up module and high-performance sign recognition module based on the Conv3D network. To achieve high-performance classification, multi-modal fusion of RGB and depth modality was used with the temporal alignment. Then, a small Croatian sign language database containing 25 different language signs for the use in smart home environment was created in collaboration with the deaf community. The system was deployed on a Nvidia Jetson TX2 embedded system with StereoLabs ZED M stereo camera for online testing. Obtained results demonstrate that the proposed practical solution is a viable approach for real-time smart home control.

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Radha, D., M. Arun Kumar, Nagarjuna Telagam, and M. Sabarimuthu. "Smart Sensor Network-Based Autonomous Fire Extinguish Robot Using IoT." International Journal of Online and Biomedical Engineering (iJOE) 17, no. 01 (January 19, 2021): 101. http://dx.doi.org/10.3991/ijoe.v17i01.19209.

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Fire explosion is among the main reasons for death in the world. The urban spaces have a lot of population, many systems have control over fire detection but not over control of fire due to lack of functionalities. The operation of the robot depends on the android application on the smartphone. It can also be communicated using Wireless fidelity technology. The motion detection technology is embedded in it, which can identify the objects or obstacles. With Arduino microcontroller and IoT technology, this robot can send emergency alerts in critical conditions, explore the compounds, and effectively check for the fire. The entire robot was contained in the sensor-based network, and if the sensors fail to detect, the robot still will operate and extinguish fire with the help of an inbuilt camera. Finally, this robot is tested for operation in automated mode and live video buffering capability.

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Shobayo, Olamilekan, Ayobami Olajube, Nathan Ohere, Modupe Odusami, and Obinna Okoyeigbo. "Development of Smart Plate Number Recognition System for Fast Cars with Web Application." Applied Computational Intelligence and Soft Computing 2020 (February 7, 2020): 1–7. http://dx.doi.org/10.1155/2020/8535861.

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Traffic law violation has been recognized as a major cause for road accidents in most parts of the world with majority occurring in developing countries. Even with the presence of rules and regulations stipulated against this, violators are still on the increase. This is due to the fact that the rules are not properly enforced by appropriate authorities in those parts of the world. Therefore, a system needs to be designed to assist law enforcement agencies to impose these rules to improve road safety and reduce road accidents. This work uses a Vehicle Plate Number Recognition (VNPR) system which is a real-time embedded system to automatically recognize license plate numbers. It provides an alternative means to VPNR using an open-source library known as openCV. The main aim of the system is to use image processing to identify vehicles violating traffic by their plate numbers. It consists of an IR sensor for detecting the vehicle. During testing, a minimum time was set for the sensor to detect the object which was recorded by the microprocessor. Once it was less than the set time, the camera was triggered to capture the plate number and store the image on the Raspberry Pi. The image captured is processed by the Raspberry Pi to extract the numbers on the image. The numbers on the capture imaged were viewed on a web page via an IP address. The system if implemented can be used to improve road safety and control traffic of emerging smart cities. It will also be used to apply appropriate sanctions for traffic law violators.

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Фахми, Ш. С., С. А. Селиверстов, Е. В. Костикова, Р. Р. Муксимова, and В. О. Титов. "Real-time marine vessel surveillance video system." MORSKIE INTELLEKTUAL`NYE TEHNOLOGII), no. 2(52) (June 5, 2021): 98–105. http://dx.doi.org/10.37220/mit.2021.52.2.015.

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Анализируется процесс развития систем наблюдения. Раскрываются особенности технологических изменений систем наблюдения 1-го, 2-го и 3-го поколений. Декларируется, что современные полупроводниковые технологии позволяют перейти к более развитым системам видеонаблюдения 3-го поколения, где преобразование и обработка видеоинформации выполняются непосредственно в видеодатчиках на этапе формирования кадров. Умные камеры расширяют функциональность видеосенсора 3-го поколения, обеспечивая бортовую высокоуровневую обработку видео. Рассмотрены эволюция систем наблюдения и архитектура обработки видеоинформации с использованием интеллектуальных видеокамер с высоким динамическим диапазоном. Представлена графическая интерпретация, иллюстрирующая процесс эволюции систем видеонаблюдения от 1-го к 3-му поколению. Проанализированы функции современных систем видеонаблюдения и переход от высокоуровневой обработки видео из систем общего назначения во встраиваемые системы. Рассмотрен состав видеосистемы наблюдения с использованием интеллектуальной видеокамеры, включающий видеодатчик, блок обработки и блок управления связи. Описаны условия в которых морские системы видеонаблюдения используются. Приведены результаты экспериментальных исследований и выполнены оценки производительности. Показаны достигнутые результаты производительности для различных реализаций алгоритма обнаружения морских судов и необходимое время выполнения при обработке одного изображения с полным разрешением на стандартном настольном компьютере Pentium 4 с частотой 2,4 ГГц. с использованием реконфигурируемой системой на кристалле. The process of development of observation systems is analyzed. The features of technological changes in observation systems of the 1st, 2nd and 3rd generations are revealed. It is declared that modern semiconductor technologies make it possible to move to more advanced third-generation video surveillance systems, where the conversion and processing of video information is performed directly in video sensors at the stage of framing. Smart cameras extend the functionality of the 3rd generation image sensor to provide on-board high-level video processing. The evolution of surveillance systems and architecture of video information processing using smart cameras with a high dynamic range are considered. A graphical interpretation is presented that illustrates the evolution of video surveillance systems from the 1st to the 3rd generation. The functions of modern video surveillance systems and the transition from high-level video processing from general-purpose systems to embedded systems are analyzed. The composition of a video surveillance system using an intelligent camera is considered, including a video sensor, a processing unit and a communication control unit. The conditions in which marine video surveillance systems are used are described. The results of experimental studies are presented and performance estimates are performed. Shown are the achieved performance results for various implementations of the ship detection algorithm and the required execution time when processing one full resolution image on a standard Pentium 4 desktop computer running at 2.4 GHz. using a reconfigurable system on a chip.

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Singh, Pankaj, Byung Wook Kim, and Sung-Yoon Jung. "Performance Analysis of Display Field Communication with Advanced Receivers." Wireless Communications and Mobile Computing 2020 (April 4, 2020): 1–14. http://dx.doi.org/10.1155/2020/3657309.

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Display field communication (DFC) is an imperceptible display-to-camera (D2C) communication approach that provides dual-mode, full-frame, visible light communication capabilities. Unlike conventional screen-to-camera communication approaches, DFC embeds data imperceptibly in the spectral domain of individual video frames. This paper analyzes the practical performance of the DFC scheme with advanced receivers, including zero forcing (ZF), minimum mean square error (MMSE), and maximum likelihood (ML). A 249×262 color image is used for embedding data consisting of eight individual information vectors with their elements 2-QAM and 4-QAM modulated. The color image is separated into three individual channels, i.e., red (R), green (G), and blue (B). A lossy display-camera channel is considered in the presence of Gaussian noise, blooming, and various geometric distortions. Simulation results show that the ML receiver outperforms MMSE and ZF receivers. In addition, independent RGB data channels are evaluated to compare the symbol error rate of each channel. The proposed color DFC algorithm can be a viable candidate for practical scenarios in applications like smart content transmission and for supporting robust communication performance with advanced receivers, while the data embedded in the images remain unobtrusive to the human eye.

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Solanes, J. Ernesto, Pau Muñoz-Benavent, Vicent Girbés, Leopoldo Armesto, and Josep Tornero. "On improving robot image-based visual servoing based on dual-rate reference filtering control strategy." Robotica 34, no. 12 (June 11, 2015): 2842–59. http://dx.doi.org/10.1017/s0263574715000454.

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SUMMARYIt is well known that the use of multi-rate control techniques have improved the performance of many systems in general, and robotic systems, in particular. The main contribution of this paper is the generalization of the Reference Filtering control strategy from a dual-rate point of view, improving its inherent properties by overcoming the problem of sensor latency. In the paper, we discuss and analyze the improvements introduced by the novel dual-rate reference filtering control strategy in terms of convergence time, reachability and robustness. More specifically, we discuss the capability to solve positioning tasks, when hardware limitations are present with large sampling rates. In addition, a comparison is made between the single-rate and the proposed dual-rate control strategies to prove the advantages of the latter approach. A complete set-up has been prepared for validation, including a six degree of freedom (DOF) industrial manipulator, a smart camera and embedded hardware used as a high level controller.

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Ratna Kamala, P., P. Pavan Kumar, and A. Anish. "Implementation of an Intelligent Door Bell System Using Internet of Things." Asian Journal of Computer Science and Technology 8, S3 (June 5, 2019): 59–62. http://dx.doi.org/10.51983/ajcst-2019.8.s3.2086.

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Security has become the most important issue in this modernized world. Especially in cases where nobody is available at home, residences dwelled with old age people and the residences of working citizens needs security as the residents and things within the home has become a severe issue of concern as many intruders are concentrating on these type of residences for easy way of earning. To eradicate such activities by the intruders to certain extent, several strategies and systems were developed and been into market. Most of the proposed smart home systems try to bring solutions for security problem, at the cost of usage of numerous sensor devices. Also threats to these security solutions are also increasing as technology is developing. Internet of Things (IoT), a giant network of connected devices is the latest technology being used everywhere. With the increasing threats to security issues, it is necessary to use such new technologies to achieve the same with increased security. This paper presents a real time Image based intelligent door system for home security that uses a pi camera. This is an efficient approach in providing security and thereby a reliable embedded system device developed utilizing the technology to meet the complex and challenging tasks. If a person clicks the door bell, picture of the person is captured and the image is sent to the owner through SMS and e-mail. Owner of the house can respond by opening the door if he is available in the house. If he is out of the house, a message is sent back to the person in the form of an audible voice and is made audible through a speaker. Proposed system offers several advantages in providing safety and security in terms of visualization and identification of people who visits the home.

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Wolf, W., B. Ozer, and T. Lv. "Smart cameras as embedded systems." Computer 35, no. 9 (September 2002): 48–53. http://dx.doi.org/10.1109/mc.2002.1033027.

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Bigazzi, Luca, Stefano Gherardini, Giacomo Innocenti, and Michele Basso. "Development of Non Expensive Technologies for Precise Maneuvering of Completely Autonomous Unmanned Aerial Vehicles." Sensors 21, no. 2 (January 8, 2021): 391. http://dx.doi.org/10.3390/s21020391.

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In this paper, solutions for precise maneuvering of an autonomous small (e.g., 350-class) Unmanned Aerial Vehicles (UAVs) are designed and implemented from smart modifications of non expensive mass market technologies. The considered class of vehicles suffers from light load, and, therefore, only a limited amount of sensors and computing devices can be installed on-board. Then, to make the prototype capable of moving autonomously along a fixed trajectory, a “cyber-pilot”, able on demand to replace the human operator, has been implemented on an embedded control board. This cyber-pilot overrides the commands thanks to a custom hardware signal mixer. The drone is able to localize itself in the environment without ground assistance by using a camera possibly mounted on a 3 Degrees Of Freedom (DOF) gimbal suspension. A computer vision system elaborates the video stream pointing out land markers with known absolute position and orientation. This information is fused with accelerations from a 6-DOF Inertial Measurement Unit (IMU) to generate a “virtual sensor” which provides refined estimates of the pose, the absolute position, the speed and the angular velocities of the drone. Due to the importance of this sensor, several fusion strategies have been investigated. The resulting data are, finally, fed to a control algorithm featuring a number of uncoupled digital PID controllers which work to bring to zero the displacement from the desired trajectory.

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Bigazzi, Luca, Stefano Gherardini, Giacomo Innocenti, and Michele Basso. "Development of Non Expensive Technologies for Precise Maneuvering of Completely Autonomous Unmanned Aerial Vehicles." Sensors 21, no. 2 (January 8, 2021): 391. http://dx.doi.org/10.3390/s21020391.

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In this paper, solutions for precise maneuvering of an autonomous small (e.g., 350-class) Unmanned Aerial Vehicles (UAVs) are designed and implemented from smart modifications of non expensive mass market technologies. The considered class of vehicles suffers from light load, and, therefore, only a limited amount of sensors and computing devices can be installed on-board. Then, to make the prototype capable of moving autonomously along a fixed trajectory, a “cyber-pilot”, able on demand to replace the human operator, has been implemented on an embedded control board. This cyber-pilot overrides the commands thanks to a custom hardware signal mixer. The drone is able to localize itself in the environment without ground assistance by using a camera possibly mounted on a 3 Degrees Of Freedom (DOF) gimbal suspension. A computer vision system elaborates the video stream pointing out land markers with known absolute position and orientation. This information is fused with accelerations from a 6-DOF Inertial Measurement Unit (IMU) to generate a “virtual sensor” which provides refined estimates of the pose, the absolute position, the speed and the angular velocities of the drone. Due to the importance of this sensor, several fusion strategies have been investigated. The resulting data are, finally, fed to a control algorithm featuring a number of uncoupled digital PID controllers which work to bring to zero the displacement from the desired trajectory.

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Chen, Andrew, Rohaan Gupta, Anton Borzenko, Kevin Wang, and Morteza Biglari-Abhari. "Accelerating SuperBE with Hardware/Software Co-Design." Journal of Imaging 4, no. 10 (October 18, 2018): 122. http://dx.doi.org/10.3390/jimaging4100122.

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Background Estimation is a common computer vision task, used for segmenting moving objects in video streams. This can be useful as a pre-processing step, isolating regions of interest for more complicated algorithms performing detection, recognition, and identification tasks, in order to reduce overall computation time. This is especially important in the context of embedded systems like smart cameras, which may need to process images with constrained computational resources. This work focuses on accelerating SuperBE, a superpixel-based background estimation algorithm that was designed for simplicity and reducing computational complexity while maintaining state-of-the-art levels of accuracy. We explore both software and hardware acceleration opportunities, converting the original algorithm into a greyscale, integer-only version, and using Hardware/Software Co-design to develop hardware acceleration components on FPGA fabric that assist a software processor. We achieved a 4.4× speed improvement with the software optimisations alone, and a 2× speed improvement with the hardware optimisations alone. When combined, these led to a 9× speed improvement on a Cyclone V System-on-Chip, delivering almost 38 fps on 320 × 240 resolution images.

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Chung, Tae-Sun, Dong-Joo Park, and Jongik Kim. "An Efficient Flash Translation Layer for Large Block NAND Flash Devices." Journal of Circuits, Systems and Computers 24, no. 09 (August 27, 2015): 1550138. http://dx.doi.org/10.1142/s0218126615501388.

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Recently, flash memory is widely used as a non-volatile storage for embedded applications such as smart phones, MP3 players, digital cameras and so on. The software layer called flash translation layer (FTL) becomes more important since it is a key factor in the overall flash memory system performance. Many researchers have proposed FTL algorithms for small block flash memory in which the size of a physical page of flash memory is equivalent to the size of a data sector of the file system. However, major flash vendors have now produced large block flash memory in which the size of a physical page is larger than the file system's data sector size. Since large block flash memory has new features, designing FTL algorithms specialized to large block flash memory is a challenging issue. In this paper, we provide an efficient FTL named LSTAFF* for large block flash memory. LSTAFF* is designed to achieve better performance by using characteristics of large block flash memory and to provide safety by abiding by restrictions of large block flash memory. Experimental results show that LSTAFF* outperforms existing algorithms on a large block flash memory.

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Dias, Fabio, François Berry, Jocelyn Sérot, and François Marmoiton. "SMART CAMERA WITH EMBEDDED TRACKING ALGORITHM." IFAC Proceedings Volumes 40, no. 15 (2007): 155–60. http://dx.doi.org/10.3182/20070903-3-fr-2921.00029.

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Heyrman, Barthélémy, Michel Paindavoine, Renaud Schmit, Laurent Letellier, and Thierry Collette. "Smart camera design for intensive embedded computing." Real-Time Imaging 11, no. 4 (August 2005): 282–89. http://dx.doi.org/10.1016/j.rti.2005.04.006.

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Loianno, Giuseppe, Yash Mulgaonkar, Chris Brunner, Dheeraj Ahuja, Arvind Ramanandan, Murali Chari, Serafin Diaz, and Vijay Kumar. "Autonomous flight and cooperative control for reconstruction using aerial robots powered by smartphones." International Journal of Robotics Research 37, no. 11 (September 2018): 1341–58. http://dx.doi.org/10.1177/0278364918774136.

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Advances in consumer electronics products and the technology seen in personal computers, digital cameras, and smartphones phones have led to the price/performance ratio of sensors and processors falling dramatically over the last decade. In particular, many consumer products are packaged with small cameras, gyroscopes, and accelerometers, all sensors that are needed for autonomous robots in GPS-denied environments. The low mass and small form factor make them particularly well suited for autonomous flight with small flying robots. In this work, we present the first fully autonomous smartphone-based system for quadrotors. We show how multiple quadrotors can be stabilized and controlled to achieve autonomous flight in indoor buildings with application to smart homes, search and rescue, monitoring construction projects, and developing models for architecture design. In our work, the computation for sensing and control runs on an off-the-shelf smartphone, with all the software functionality embedded in a smartphone app. No additional sensors or processors are required for autonomous flight. We are also able to use multiple, coordinated autonomous aerial vehicles to improve the efficiency of our mission. In our framework, multiple vehicles are able to plan safe trajectories avoiding inter-robot collisions, while concurrently building in a cooperative manner a three-dimensional map of the environment. The work allows any consumer with any number of robots equipped with smartphones to autonomously drive a team of quadrotor robots, even without GPS, by downloading our app and cooperatively build three-dimensional maps.

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Kokadwar, Ishan, Anurag Kukarni, Vaibhav Limbhore, Sayali Khare, and Swati Chandurkar. "Camera based Smart Surveillance System." International Journal of Computer Applications 175, no. 17 (September 17, 2020): 20–23. http://dx.doi.org/10.5120/ijca2020920679.

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Vesnin, E. N., A. E. Mikhailov, V. A. Tsarev, and P. S. Cherkas. "Smart camera adaptive optoelectronic system." Pattern Recognition and Image Analysis 22, no. 3 (September 2012): 406–11. http://dx.doi.org/10.1134/s1054661812020216.

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Patil, Ambrish. "Smart Greenhouse using Embedded System." International Journal for Research in Applied Science and Engineering Technology 7, no. 5 (May 31, 2019): 3436–41. http://dx.doi.org/10.22214/ijraset.2019.5563.

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Korde, Saurabh, Akshay Waghmare, Abhijeet Inamdar, and Akshay Jadhav. "Embedded based smart home automation system." IJARCCE 5, no. 12 (December 30, 2016): 142–43. http://dx.doi.org/10.17148/ijarcce.2016.51230.

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Zarezadeh, Ali Akbar, Christophe Bobda, Franck Yonga, and Michael Mefenza. "Efficient network clustering for traffic reduction in embedded smart camera networks." Journal of Real-Time Image Processing 12, no. 4 (April 8, 2015): 813–26. http://dx.doi.org/10.1007/s11554-015-0498-2.

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Journal articles on the topic 'Smart camera embedded system'

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