Cloud to Edge: Is It the Center Stage of Real-Time Decision Making?

Edge computing, a location-sensitive, distributed instantaneous data processing and analysis paradigm is disrupting traditional and inefficient cloud-based systems and transforming their business operations by unlocking the value of data & fostering innovation.

According to research conducted by Precedence Research published in 2022, the edge computing market was valued at US$40.49 billion in 2021 and is expected to hit US$116.5 billion by 2030 considering a CAGR of 12.46% between 2022 and 2030 (Precedence Research, 2022).

Insight into Edge

As the amount of data traversing the world increases monumentally, conventional cloud-based systems which rely on centralised data centers are becoming increasingly obsolete. In contrast, edge computing transfers important data and resources out of data centers and closer to the source of data collection. As a result, the collected data is processed and analysed at the point of collection and is then sent back to data centers for review and further processing if required, thereby drastically reducing the workload of a centralised cloud server and amplifying the speed at which real-time decision making occurs.

This is just the beginning

Edge computing is expected to hold a valuation of approximately US$200 billion in hardware by 2025, with the logistics and transportation fields experiencing the most investment at US$35 billion followed by cross verticals at US$32 billion (Chabas, Gnanasambandam, Gupte, & Mahdavian, 2018).  

Edge computing is driving a transformation across various industries. Some of them are outlined below. 

Manufacturing – Edge computing enables expeditious automation of machines by processing data pertaining to robotics and machine interfaces at the source, leading to reduced latencies and increased production.

Transportation – It enables quick response times through rapid data processing, allowing for smoother traffic flows and better public transport connectivity.

Retail – The technology enables augmented reality for virtually trying out apparel, smart checkout experiences without the need for cashiers. It enables real-time analysis of customer population at outlets to optimise retail personnel deployment within outlets.

Farming – Farms and greenhouses will be able to analyse soil water content and crop health, reducing wastage and making cultivation a more sustainable process.

Mobile networks – Network providers will be able to offer faster upload and download speeds, wider network coverage areas, and increased network reliability to customers through edge computing.

Internet of Things – IoT devices like Amazon Alexa will be able to respond to commands quicker while allowing enhanced capabilities like turning off all electronic devices with a single voice command. Smart homes will become smarter owing to the increased security and cost advantages that edge brings to the table (STL Partners, n.d.).

Medical – Medical institutions will be able to free up their central server load and manage data effectively, leading to augmented decision-making encompassing treatment plans, resource mobilisation, and advanced infection tracking (Olavsrud, 2022).

Natural disaster management – Edge helps in streamlining the entire process due to a proliferation of forecasting and interpretation speeds. Threat information can be obtained quickly and accurately which greatly benefits threat management systems around the world, thereby supporting decision-making regarding evacuation and post-disaster management efficiently and effectively.

Streaming – Netflix made the switch to edge computing through several micro-data centers located around the world, significantly reducing latency, buffering, and improving streaming quality, giving the company an edge over its competitors through real-time customer viewing analysis and targeted recommendations (Jaylin, 2021). 

Business operations – Businesses can expect to manage crisis situations more methodically as companies can ascertain their current market performance and take decisions that allow them to adapt to the changing external environment rapidly.

The future

The BFSI industry is expected to utilise edge computing to improve speed and security through real-time facial recognition, fraud detection, and thwarting malicious attempts to manipulate code. 

Automobile manufacturers are investigating applications in vehicle management systems for self-driving, collision avoidance, and object detection while governments are expected to use it for monitoring the installation of new charging stations around countries. 

Drones will also be using the edge to feed traffic and crime information to law enforcement authorities (Nerurkar, 2022). 

As the number of industries adopting edge computing technologies progressively increases, edge computing offers the solution for surmounting existing business challenges, paving the way for more advanced ecosystems to keep up with the dynamic world.


Precedence Research. (2022, July 7). Edge Computing Market Size to Hit at USD 116.5 Billion by 2030. Retrieved from GlobeNewswire:

Chabas, J. M., Gnanasambandam, C., Gupte, S., & Mahdavian, M. (2018, November 8). New demand, new markets: What edge computing means for hardware companies. Retrieved from McKinsey:

STL Partners. (n.d.). 10 Edge computing use case examples. Retrieved from STL Partners:

Olavsrud, T. (2022, July 25). District Medical Group transforms its approach to data management. Retrieved from CIO:

Jaylin, B. (2021, December 27). Edge Computing Explained. Retrieved from OTAVA:, D. (2022, July 12). EDGE COMPUTING: 2022 WILL BE A PIVOTAL YEAR FOR EDGE ADOPTION. Retrieved from nasscom:

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