The Technological Shift: AI in Big Data and IoT

Sharma, Deepti; Singh, Amandeep; Singhal, Sanyam

doi:10.1002/9781119761655.ch4

Cited by 5 publications

(1 citation statement)

References 61 publications

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“…Analytics of Things (AoT) is the process of collecting, processing, analyzing, and deriving insights from the massive volumes of data generated by IoT devices [12]. As IoT generates a tremendous amount of data, AoT focuses on extracting meaningful information from this data to make data-driven decisions and gain actionable insights.…”

Section: Analytics Of Things (Aot)mentioning

confidence: 99%

Clarity of Knowledge Gap Between IoT and AoT - Professionals’ Perspectives

2023

IJFMR

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In this era, we have the basic idea of “Internet of Things”. We know that IoT refers to the vast network of interconnected physical devices or "things" that are embedded with sensors, softwares, and other technologies to collect and exchange data over the internet. These "things" can be anything from household appliances and industrial machines to wearable devices and vehicles. But what will be the outcome if the word “Analytics” added in the place of the word “Internet” and will be attached with the word “things” and will be termed as “Analytics of Things”? Will it be as similar as Internet of Things or it will be completely different from Internet of Things? Shall there be any other functionalities related to “things” associated with the word “Analytics”? Will it require Internet? This research paper will answer all the questions.

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Section: Analytics Of Things (Aot)mentioning

confidence: 99%

Clarity of Knowledge Gap Between IoT and AoT - Professionals’ Perspectives

2023

IJFMR

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Review of Big Data Analytics

Soni¹,

Baghel²,

Paliya³

et al. 2023

2023 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS)

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A systematic review of artificial intelligence in mathematics education: The emergence of 4IR

Opesemowo,

Adewuyi

2024

EURASIA J Math Sci Tech Ed

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The integration of artificial intelligence (AI) in mathematics education, focusing on its implications in the 4<sup>th</sup> Industrial Revolution (4IR) era. Through a comprehensive analysis of 10 relevant studies in Scopus and Google Scholar from 2015 to 2023, this review identifies the research methods, research instruments, participants, and AI tools used in mathematics education. Some key ideas include using AI-driven personalized learning and enhanced mathematics instruction, real-time assessment and feedback, curriculum development, and empowering educators, which were highlighted. The study aligns with the preferred reporting items for systematic reviews and meta-analysis. Based on the analysis, most studies reviewed utilized qualitative research methods. The study indicates that questionnaires were mainly used to gather data from students and teachers who were the most significant participants in the reviewed papers. Further results revealed that ChatGPT were the primary AI tool used in mathematics education, among other AI tools, as identified in this review. Additionally, this review discusses the transformative potential of AI in addressing educational disparities and preparing learners for the demands of 4IR.

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The Technological Shift: AI in Big Data and IoT

Cited by 5 publications

References 61 publications

Clarity of Knowledge Gap Between IoT and AoT - Professionals’ Perspectives

Clarity of Knowledge Gap Between IoT and AoT - Professionals’ Perspectives

Review of Big Data Analytics

A systematic review of artificial intelligence in mathematics education: The emergence of 4IR

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