By incorporating edge computing, healthcare and manufacturing sectors are reaping the maximum benefits.

Edge computing is the new technique through which data can be accumulated, analyzed, handled and stored effectively. Gartner defines edge computing as “Part of a distributed computing topology where information processing is located close to the edge, where things and people produce or consume that information.”

With increased adoption and implementation of IoT devices across the industry, organizations are readily incorporating edge computing for efficacy and cost-effectiveness in data management. In edge computing, data gets processed closer to the data storage space of the devices, instead of a far-away central location such as the cloud. Edge computing scales up the performance of the devices and application by eliminating the latency issue associated with traditional data management tools. The global edge computing market size is forecasted to grow from US$3.6 billion in 2020 to US$15.7 billion by 2025 at a CAGR of 34.1% during the forecast period.

A report by PwC states that for sustaining the disconnected cloud option, across the industry, edge computing will be the best feasible option in the coming decade. As sectors are advancing to deploy this nascent technology, healthcare and manufacturing sectors are respectively reaping the maximum benefits with edge computing.

Edge computing in the Medicine

Edge computing addresses the pre-existing challenges in the healthcare sector. Currently, healthcare faces a major challenge in delivering diagnosis and treatment services to remote and rural communities. Many instances have been constantly cited and published, where a delay or lack of medical treatment ensued fatalities. This is specifically prominent in South-Asian and African countries, where the resources are scarce, medical facilities unequipped and connectivity lapsed to prevent the rural population from fatal disease outcomes. Henceforth, integration of edge computing in IoT healthcare devices such as glucose monitors, heart rate monitor and connected inhalers, amongst others, will not only diagnose the chronic diseases but will also alert the authorities regarding the prominence of such conditions in an area, for effective treatments. For example, the glucose meter is indicative of the increase of sugar level in the human body. The local hospital can monitor glucose-level across the middle-aged population in villages and the results generated will lead to the effective delivery of drugs for diabetes across the rural population.

Edge computing enhances the patient experience in healthcare set-up. For instance, owing to COVID 19, many blood-sugar patients get inclined to treatment that doesn’t require them to visit a hospital. Many healthcare institutes are offer tele-medicines, but without the data about patients, no effective diagnosis and treatment plan gets formulated.

Incorporating edge computing across IoT wearable devices such as heart monitor and glucometer will provide effective diagnosis and treatment of diseases at home, thus eliminating the risk of visiting a hospital during uncertain times.

Medtech companies grapple with the challenge of maintaining security while deploying AI-enabled medical devices across institutes. With a significant increase in data breach and ransomware, many healthcare institutes are reluctant to employ tools that cause security infringement. This becomes a major concern for research of new diseases and techniques. Henceforth, incorporating edge computing in AI-enabled devices will help in data management and processing locally, while delivering cost-effective solutions, along with complying with the medical policies.

Edge Computing in Manufacturing

The manufacturing sector is constantly faced with the challenge of multi-dimensional improvement in products and services. With the wave of digital transformation, manufacturing is the first sector to adopt disruptive technologies. Henceforth, edge computing is readily driving innovation across the manufacturing sector.

Implementation of edge computing across manufacturing plants and units ensure condition-based monitoring. This implies that even when the warehouses, plants and units are located remotely, data can be extracted from remote machines using edge computing, to draw powerful insight about the system.

Edge computing also readily detects the discrepancies in the servers and processes of a system. In a traditional system, detecting the damages and faults is a time-consuming task. Additionally, discrepancy across the servers and networks is indicative of possible security infringement and data breach. This challenges the cybersecurity across the entire unit and plant if detecting the fault takes long. By incorporating edge computing, the accurate and faster predictive solution is enabled to the problem existing in the system.

Wrapping up

Edge computing is a powerful tool for promising effective results. With a surge in data generation, organizations must employ edge computing for faster and accurate outcomes.