Sensors for Monitoring Components, Systems and Processes

Jayakumar, T.; Rao, C. Babu; Philip, John; Mukhopadhyay, C. K.; Jayapandian, J.; Pandian, C. K. Arvinda

doi:10.21307/ijssis-2017-379

Cited by 9 publications

(10 citation statements)

References 10 publications

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“…By testing the bit error rate of the system through experiments in different environments, different distances of the communications test, we learn the channel bit error rate of the system is 2 10 , the transmission is at a distance of 500~1200m, the average bit error rate is between 56 10~10 . On the actual test of Springs Road landslide, supposing sending data frame x, y frame is received, that is when sending11 x , 11 y is correctly received, then get the monitoring data of landslide, and according to the formula (1) to calculate the bit error rate, as shown in table 1.…”

Section: B Data Processing and Analysis For Results Of Landslide Monimentioning

confidence: 99%

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The Reseach on Wireless Sensor Network for Landslide Monitoring

Zhang

2013

International Journal on Smart Sensing and Intelligent Systems

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Section: B Data Processing and Analysis For Results Of Landslide Monimentioning

confidence: 99%

“…The improvement can not only improve accuracy of monitoring but also contribute to more precise generation process of landslide. Similarly, improvement on monitoring equipment also facilitates to lower cost and promotes application of monitoring system [2].…”

Section: Introductionmentioning

confidence: 99%

The Reseach on Wireless Sensor Network for Landslide Monitoring

Zhang

2013

International Journal on Smart Sensing and Intelligent Systems

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“…Recognizing human activities from ambient and physiological sensors has attracted lot of research interest recently [1,2]. The application of sensors encompasses many sectors of industry [3]; the multiple sensor fusion method plays a major role in application [4]. The multisensory information fusion technology mainly aims to solve the information processing problems, which focuses on the using the information derived by multiple sensors to constructcomplete and proper description on the special object or environment features [5,6].Recent years witnessed an increased interest in computational models that mimic the human sensing perception [7].…”

Section: Introductionmentioning

confidence: 99%

Detection and classification of the behavior of people in an intelligent building by camera

Ahmed

Faouzi

Caelen

2013

International Journal on Smart Sensing and Intelligent Systems

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Abstract-an intelligent building is an environment that contains a number of sensor and camera, which aims to provide information that give the various actions taken by individuals, and their status to be processed by a system of detection and classification of behaviors . This system of detection and classification uses this information as input to provide maximum comfort to people who are in this building with optimal energy consumption, for example if I workout in the room then the system will lower the heating . My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use RGB color histograms INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS VOL. 6, NO. 4, SEPTEMBER 2013 1317 and textures for LBP represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for the detection and classification of the behavior of people in this intelligent building in order to give maximum comfort with optimized energy consumption. The classification is performed using the classification of k 1 and k = 11 in our case, we built 11 models in the learning phase using different nucleus in order to choose the best models that give the highest classification rate and finally for, the classification phase, to classify the behavior, we compare it to the 11 behaviors, that is to say, we make 11 classification and take the behavior that has the highest classification rate. This work has been carried out within the University Joseph Fourier in Grenoble precisely LIG (Grenoble computer lab) in the team MULTI COM and the University of Oran Algeria USTO. Our contribution in this field is the design and implementation of a robust, and accurate system that make detection and classification of 11 behaviors cameras in an intelligent building, varying illumination it means, whatever lighting is our system must be capable of detecting and classifying behaviors.

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“…The Wireless Smart City (WSC) is one of the important components in Smart Grid and Internet of Things, attracting increasing attentions in the engineering field [1] [2]. With the advantage of distribution information aggregation and remote device management provided by thousands of sensors and controllers [3] [4], potential challenges for the system design (such as large scale of network, limited resources, sensor heterogeneity, unreliability of changing topology, and data delay) are emerging as well. Field test provides an effective way for designers to accurately evaluate the whole system and gives powerful verification for the subsequent improvements.…”

Section: Introductionmentioning

confidence: 99%