3D Thermal Monitoring and Measurement using Smart-phone and IR Thermal Sensor

Saha, Arindam; Dewangan, Keshaw; Dasgupta, Ranjan

doi:10.5220/0005786106940700

Cited by 2 publications

(5 citation statements)

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“…Many papers proposed new approaches to improve the performance for 3D thermal model reconstruction in terms of computational time as well as precision of the model. References [ 10 , 51 ] described two new approaches that improved the computational time for the generation of the 3D model but failed to improve the accuracy of the 3D model. All these approaches require manual calibration of the camera using the checkerboard method proposed by [ 13 ] to calculate parameters of the camera.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Outlier points reduce the accuracy of the 3D model. To remove the outliers, reference [ 8 ] used Random Sample Consensus (RANSAC), reference [ 52 ] used M-estimator Sample Consensus (MSAC) which is a variation of RANSAC, reference [ 10 ] used epipolar geometry and epipolar constraints, reference [ 51 ] improved Belief propagation algorithm to optimize the outlier detection technique and reference [ 50 ] did not use any outlier detection technique which resulted in increased computational time as there are more points for 3D reconstruction. After getting a pair of images, a point in 3D is constructed using different methods.…”

Section: Literature Reviewmentioning

confidence: 99%

“…After getting a pair of images, a point in 3D is constructed using different methods. References [ 8 , 50 , 52 ] proposed to use structure from motion (SFM) to create a point in 3D space, whereas references [ 10 , 51 ] used concepts of epipolar geometry to calculate the coordinates in 3D space. Both approaches create a sparse or dense 3D model depending upon the number of images provided.…”

Section: Literature Reviewmentioning

confidence: 99%

“…For example, to detect heat or energy leakage around an electrical appliance, one more dimension of depth is needed. Modeling the 3D thermal model enables us to measure energy performance [ 8 ] and to perform volumetric heat measurement [ 10 ]. A 3D thermal model consists of 3D points, reconstructed from images of a scene, with the corresponding temperature value.…”

Section: Introductionmentioning

confidence: 99%

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Activity Recognition in Residential Spaces with Internet of Things Devices and Thermal Imaging

Naik

Pandit

Naik

et al. 2021

Sensors

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In this paper, we design algorithms for indoor activity recognition and 3D thermal model generation using thermal images, RGB images, captured from external sensors, and the internet of things setup. Indoor activity recognition deals with two sub-problems: Human activity and household activity recognition. Household activity recognition includes the recognition of electrical appliances and their heat radiation with the help of thermal images. A FLIR ONE PRO camera is used to capture RGB-thermal image pairs for a scene. Duration and pattern of activities are also determined using an iterative algorithm, to explore kitchen safety situations. For more accurate monitoring of hazardous events such as stove gas leakage, a 3D reconstruction approach is proposed to determine the temperature of all points in the 3D space of a scene. The 3D thermal model is obtained using the stereo RGB and thermal images for a particular scene. Accurate results are observed for activity detection, and a significant improvement in the temperature estimation is recorded in the 3D thermal model compared to the 2D thermal image. Results from this research can find applications in home automation, heat automation in smart homes, and energy management in residential spaces.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Activity Recognition in Residential Spaces with Internet of Things Devices and Thermal Imaging

Naik

Pandit

Naik

et al. 2021

Sensors

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“…Initial work with handheld smart-phone based system is presented in [34]. FLIR thermal attachment with a smartphone is mounted on the Firebird VI robotic platform and it is calibrated.…”

Section: Proposed Integrated Sensing Systemmentioning

confidence: 99%

Human-Like Sensing for Robotic Remote Inspection and Analytics

Pal

Dasgupta

Saha

et al. 2016

Wireless Pers Commun

Self Cite

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In this paper we introduce Human-like Sensing or ''5 senses computing'' as a natural futuristic extension of Internet-of-Things. We discuss how 3D optical vision, thermal vision, acoustic profiling, olfaction and tactile sensing can help in remote inspection and analytics solutions. We propose a robot mounted opto-thermal and acoustic sensing system as a possible integrated system to gather such data. We present results of field experiments conducted with the proposed system and show how such systems can provide acceptable solutions for remote inspection and analytics.

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3D Thermal Monitoring and Measurement using Smart-phone and IR Thermal Sensor

Cited by 2 publications

References 0 publications

Activity Recognition in Residential Spaces with Internet of Things Devices and Thermal Imaging

Activity Recognition in Residential Spaces with Internet of Things Devices and Thermal Imaging

Human-Like Sensing for Robotic Remote Inspection and Analytics

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