Detection of Posture Using MS-IoT-Based Solution to Provide Timely Treatment

Detection of Posture Using MS-IoT-Based Solution to Provide Timely Treatment

Sandeep Bhatia, Basetty Mallikarjun, Neha Goel, Divye Dandeva, Neetu Sharma, Bharat Bhushan Naib
Copyright: © 2024 |Pages: 36
DOI: 10.4018/979-8-3693-1910-9.ch010
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Abstract

An extremely potent AI solution for animal care is created when Microsoft Custom Vision Service is combined with Azure IoT stack, particularly in hospitals with a shortage of monitoring manpower. The GUI and configuration files for Azure logic apps are unique. Here are various human charity and animal care charity agencies across who need an intelligent solution which can help them in continuous monitoring of animals in the process of their treatments. Human and animal posture detection is an intelligent care solution in India. It is designed using Microsoft technology stack. The whole idea behind the solution is to provide continuous monitoring of humans and animals in the hospital. And in case any improper gestures/postures are detected, then the solution can inform concerned doctors or care takers through mobile alerts. In this chapter, the authors have proposed architecture for hospital monitoring and this system has been implemented in real-time.
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1. Introduction

Posture detection is an intelligent Human and Animal Care solution for all the charity and non-charity animal hospitals in India. It is designed using Microsoft technology stack. The whole idea behind the solution is to provide continuous monitoring of animals in the hospital. And in case, some improper gestures/postures are detected in Animals then the solution can inform concerned doctors or care takers through mobile alerts.

Animal care hospitals usually deploy human resources to take care of animals. It becomes responsibility of the taking care person to continuously monitor animals which are in critical stage.

Usually such duties are performed in shifts. When one set of hospital staff is done with 8 or 9 hours of job they are replaced by another set of hospital staff to perform next 8-9 hours of monitoring.

Intelligent Animal Care and Healthcare using posture detection can perform such monitoring 24*7 with very minimal amount of support of human intervention. If IAC sees any abnormality it quickly informs the hospital staff. So, IAC can decrease the demand of staff which does the job of monitoring only.

1.1 Artificial Intelligence

Artificial intelligence is the intelligence that computer machines try to exhibit. As we know human minds are very powerful. Human mind is capable of learning by sensing the environment. Sometime, when human mind meets a situation which it has never experienced before, it still tries to attempt best possible approach to it and most of the succeeds.

Artificial intelligence is technique where in computer machines try to mimic human mind.

Human mind uses different techniques to learn and increase its intelligence. Similarly, Artificial experts have designed and derived different algorithms and techniques to make computer intelligence more intelligent.

1.2 Machine Learning

Machine learning is technique in which a machine tries to learn the things based on inputs, inputs & outputs both or incomplete input and output data.

Just like a human mind gets its training form the day a human is born, similarly machines also try to learn.

1.3 Machine Learning Approaches

1.3.1 Supervised Learning

In Supervised learning a machine is provided with complete training data set means while learning machine knows what the output value for a particular input should be.

1.3.2 Semi Supervised Learning

In semi-supervised learning, machine is provided with half training data set. It has derived conclusions based on limited dataset only.

1.3.3 Un_Supervised Learning

In case of un-supervised learning, only input data is given to the machine learning algorithm and it has to derive the output from it by its own.

1.3.4 Reinforcement Learning

In reinforcement learning, a machine works as a learning agent which attempts to learn from environment and each of its resulting action is given a score. Every action that results in less score causes the algorithm to try another approach next time.

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