Virtual motion and pose from images and video can be estimated by detecting body joints and their interconnection. The human body has diverse and complicated poses in yoga, making its classification challenging. This study estimates yoga poses from the images using a neural network. Five different yoga poses, viz. downdog, tree, plank, warrior2, and goddess in the form of RGB images are used as the target inputs. The BlazePose model was used to localize the body joints of the yoga poses. It detected a maximum of 33 body joints, referred to as keypoints, covering almost all the body parts. Keypoints achieved from the model are considered as predicted joint locations. True keypoints, as the ground truth body joint for individual yoga poses, are identified manually using the open source image annotation tool named Makesense AI. A detailed analysis of the body joint detection accuracy is proposed in the form of percentage of corrected keypoints (PCK) and percentage of detected joints (PDJ) for individual body parts and individual body joints, respectively. An algorithm is designed to measure PCK and PDJ in which the distance between the predicted joint location and true joint location is calculated. The experiment evaluation suggests that the adopted model obtained 93.9% PCK for the goddess pose. The maximum PCK achieved for the goddess pose, i.e., 93.9%, PDJ evaluation was carried out in the staggering mode where maximum PDJ is obtained as 90% to 100% for almost all the body joints.
Data acquisition and controlling (DAC) system refers to provide solution which is capable of making measurement and controlling external processes using variety of hardware and software. The proposed design and its implementation of DAC system based on the freeRTOS platform. The suggested system is used to monitor and control industrial applications. The proposed system is design on open source hardware Arduino platform in which freeRTOS Application programming Interfaces (APIs) is installed and configured. As part of the hardware, here three basic sensors are used as temperature sensor for measuring temperature, flame sensor as measuring the flame and ultrasonic sensor as measuring the water level in the tank. Buzzer and LEDs are used as the controlling devices for flame sensor, whereas motor is used as the controlling device for ultrasonic sensor. Here temperature sensor is used as monitoring device. The proposed system can justify the remote monitoring and controlling task through the network using the web browser. The proposed system continuously monitors the sensor values and displays it onto the web browser. If the sensor value is exceeds from the threshold values, it will take necessary controlling actions.
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