# Fostering new Vertical and Horizontal IoT Applications with Intelligence Everywhere

arXiv: https://arxiv.org/abs/2310.00346 · HTML: https://mlsanity.com/paper/2310.00346/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Sep 2023.

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

- [Artificial Intelligence for Collective Intelligence: A National-Scale Research Strategy](https://mlsanity.com/paper/2411.06211/) (2024)
- [ECAvg: An Edge-Cloud Collaborative Learning Approach using Averaged Weights](https://mlsanity.com/paper/2310.03823/) (2023)
- [Achieving Pareto Optimality using Efficient Parameter Reduction for DNNs in Resource-Constrained Edge Environment](https://mlsanity.com/paper/2403.10569/) (2024)

## Abstract (arXiv)

Intelligence Everywhere is predicated on the seamless integration of IoT networks transporting a vast amount of data streams through many computing resources across an edge-to-cloud continuum, relying on the orchestration of distributed machine learning models. The result is an interconnected and collective intelligent ecosystem where devices, systems, services, and users work together to support IoT applications. This paper discusses the state-of-the-art research and the principles of the Intelligence Everywhere framework for enhancing IoT applications in vertical sectors such as Digital Health, Infrastructure, and Transportation/Mobility in the context of intelligent society (Society 5.0). It also introduces a novel perspective for the development of horizontal IoT applications, capable of running across various IoT networks while fostering collective intelligence across diverse sectors. Finally, this paper provides comprehensive insights into the challenges and opportunities for harnessing collective knowledge from real-time insights, leading to optimised processes and better overall collaboration across different IoT sectors.