Patient care is transformed when AIOT is included into contemporary healthcare. The influence of AIOT on remote patient monitoring is examined in this chapter, with a focus on how it may improve healthcare outcomes. Real-time monitoring of vital signs, activities, and mental health is made possible by wearable AIOT devices. Data on blood oxygenation, temperature, respiration, and heartbeat are analyzed using sensor nodes and machine learning. Using RPM, the AIOT architecture gathers a variety of biological data and sends it to the IoT cloud for extensive patient monitoring. Examined for their contributions to patient care are a variety of AIOT healthcare products, including wearables, robotic surgical equipment, blood clotting testing devices, linked inhalers, depression monitoring wristwatch applications, and IoT-connected contact lenses. The chapter demonstrates AIOT's potential to improve patient outcomes and support a more efficient and accessible healthcare system by highlighting its role in early identification, particularly for life-threatening disorders.
Top1. Introduction
The aim of this remote patient monitoring system is to construct healthcare that is more efficient, effective, successful, and easily accessible to a larger population. With the help of AI and the Internet of Things, a patient can be monitored with accurate disease prediction, and illness can be detected within seconds. The aim to start this remote patient monitoring with AIOT is to provide accurate predictions for many life-threatening diseases like cancer and heart disease at early stages so that they can be cured. In some developing countries, there is a shortage of doctors, due to which treatment is not being provided properly due to a lack of time. In such a condition, it is really challenging for patients and elderly people to take appointments and get proper treatment. Another problem is the restriction on visiting doctors during the pandemic. To address this issue, we are developing an intelligent remote health monitoring system for patients based on artificial intelligence, which will allow patients to consult with a doctor and receive treatment via digital mode. An intelligent remote patient activity tracking system helps monitor patient activities and check those activities based on the attached sensors. An artificial Internet of Things (IoT) enabled health monitoring device is implemented and designed using various machine learning models to keep a record of the patient’s activities, such as sleeping, walking, running, and exercising, the necessities during those activities, such as body temperature and heart rate, and the patient’s breathing pattern during such activities(Talukder & Haas, 2021).
Machine learning models are used for the identification of different activities of the patient and for detecting the patient’s breathing, respiratory health, and vitals during various activities. Recently, various AI and machine learning models have been used to detect cough and breathing problems.
1.1 Artificial Intelligence of Things
Artificial intelligence of things (AIOT) is defined as the blend or combination of artificial intelligence technologies along with the Internet of Things framework. The main goal of AIOT is to implement and perform more efficient IoT functionalities and operations, as well as to improve human and machine interactions and enhance management of data and its analysis with ease. AI is the simulation of human intelligence processes by machines, especially computer systems, and is typically used in natural language processing (NLP), speech recognition, and machine learning vision. IoT consists of many interconnected things with built-in sensors and has the power to generate and collect a huge amount of data. This data can be easily analyzed and utilized with artificial intelligence for solving problems based on decision-making. AI can enhance the value of IoT (Janaki & Sravanthi, 2022). For instance, machine learning is one of the most utilized key technologies to be used for AIOT.
AI implementation in the field of healthcare aids in enhancing and improving the quality and effectiveness of patients' decision-making processes. Its implementation along with the IoT helps in treating patients remotely with accurate and complete health information about the patient and providing real-time data. The remote patient monitoring system can present an effective solution to control and monitor a vast number of patients and maintain their data. Artificial intelligence and the Internet of Things (IoT) are the cutting-edge technologies that allow electronic devices to perform tasks like human beings. These tasks include understanding abilities, thinking, implementing, making decisions, and solving problems (De Michele & Furini, 2019). Machine learning, deep learning, ambient intelligence, smart objects, big data, data analytics, embedded systems, blockchain, and other techniques are used to implement AIOT.
Overall, AIOT has the potential to transform healthcare by improving patient outcomes, increasing efficiency, and reducing costs (Dhaka et al., 2022). However, it's important to ensure that these technologies are implemented in a way that maintains patient privacy and security.