AI Technology in Lifestyle Monitoring: Futuristic View – AI Technology and IoT

Introduction

Artificial intelligence is a broad section of computer science and applications. It is the process of making the machines think and act like a human being and also considered as the process of simulating the tasks and workloads concerning living beings (Yasaswini, 2018). AI has given raise to various applications by creating cognitive and intelligent machines which are trying to reduce the iterative and heavy computational intelligence tasks. These applications are employed in various fields such as gaming, arts, manufacturing industries and so on(Vickranth et al., 2019).

Figure 1.

AI is Everywhere

The above fig 1., clearly explains the applications and services in all the business domains. With the help of predictive analytics techniques, the future sales, products and Return on Investment of any business is sensed earlier. Using AI, the learning skills, problem-solving skills and reasoning skills are applied to machines or objects (Sailaja & Madhu Kanth, 2020). The algorithms and instructions are being programmed to create AI intelligent agents to solve real-world problems.

1. Composition Of Ai

This AI technology is the composition of factors such as sociology, computer science, psychology, biology, neuron science and maths (Singh & Singh, 2015). These factors are really helping to get the improved results in AI related algorithms. The below diagram 2. is narrating the importance of factors for consideration of AI based decision making process.

Figure 2.

Factors of AI

2. Ai In Email Classification

Email communication is used for sharing the information’s, advertisements and confidential information’s of any businesses. If any service provider wants to send the offer details about products, the recipients will discard those mails into spam folders (Saikumar et al., 2020).

Consider the bank application scenario, enormous of customer data have been stored and accessed often. It is considered as a tedious task to do. So AI based auto scheduled mails are sent with regular intervals (Sarat Kumar et al., 2019).

Classifying those mails are considered one of the challenge in banking sectors. Hence, the AI based classification algorithms are applied to predict and segregate these mails efficiently (Anguraj et al., 2021).

Figure 3.

Email Classification using AI Algorithms

Supervised algorithms are applied to deal with the labelled data with features attributes (Zhang, 2021). Such as regression analysis, decision tree classifier, random forest, support vector machine and logistic regression are being used widely. If the dataset has the two variables, then regression techniques are applied to extract the relationship between response variable and predictor variable. The below table 1. gives the report of spam classification results.