# Big Data Analytics for Manufacturing Internet of Things: Opportunities, Challenges and Enabling Technologies

arXiv: https://arxiv.org/abs/1909.00413 · HTML: https://mlsanity.com/paper/1909.00413/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Sep 2019.

## Built on by (most cited first, 3 of 3)

- [Artificial Intelligence-Driven Customized Manufacturing Factory: Key Technologies, Applications, and Challenges](https://mlsanity.com/paper/2108.03383/) (2021)
- [An Enhanced Randomly Initialized Convolutional Neural Network for Columnar Cactus Recognition in Unmanned Aerial Vehicle Imagery](https://mlsanity.com/paper/2105.04430/) (2021)
- [SRT: Super-Resolution for Time Series via Disentangled Rectified Flow](https://mlsanity.com/paper/2606.07605/) (2026)

## Abstract (arXiv)

The recent advances in information and communication technology (ICT) have promoted the evolution of conventional computer-aided manufacturing industry to smart data-driven manufacturing. Data analytics in massive manufacturing data can extract huge business values while can also result in research challenges due to the heterogeneous data types, enormous volume and real-time velocity of manufacturing data. This paper provides an overview on big data analytics in manufacturing Internet of Things (MIoT). This paper first starts with a discussion on necessities and challenges of big data analytics in manufacturing data of MIoT. Then, the enabling technologies of big data analytics of manufacturing data are surveyed and discussed. Moreover, this paper also outlines the future directions in this promising area.