Over the Edge: Taking IoT to the Next Level with Edge Computing

With the predetermined of over 30 billion IoT devices being deployed worldwide by 2020, the amount of data store in the cloud service is simply beyond imagination. Not to mention how huge the power needed to process and obtain tangible value from it. This, of course, pushes business professionals to look for new ways to improve their performance. One of the methods to do so is by handling and maintaining the data outside the main cloud or its “edge.” We foresee this as the next IoT trend.

Today’s tech devices take benefits from cloud computing services. However, edge computing gives more value to customers and IoT manufacturers. This article will tell you how edge computing can improve the way IoT works once the infrastructure and system matures.

Robust Data Processing

On applications and devices using computer vision or machine learning such as identity verification system or drone tracking, device-to-cloud data travel speed is relatively slower than edge computing. On-device machine learning can enhance natural language interface, allowing the smart devices to interpret voice instructions and run basic commands like turning lights on or off. Processing data at the edge reduces latency, and connected applications and devices become more responsive. Moreover, this system allows over-the-air updates for the device software and the list of local commands it can run.

Reduce Connectivity Cost

Edge computing delivers tangible value in consumer and industrial IoT use cases. Instead of sending raw streams of data obtained from sensors, edge computing sends only the information that matters which is valuable on LTE-based connected devices such as smart meters or asset trackers. Also, when facing a massive amount of data produced by sensors in an industrial facility or a mining site, the ability to analyze and filter data before sending it to a platform can lead to huge savings in network and computing resources.

Improved Security and Privacy

By storing sensitive data within the device using edge computing, security and privacy levels on IoT devices can be improved. For instance, retail advertising systems like digital signage are created to deliver specific, targeted ads and information based on target audience parameters set on field devices. The implementation of edge computing helps protect user privacy by anonymizing, analyzing, and storing the data at the main source instead of sending it to the cloud.

It’s not difficult to see why edge computing is considered as one of the key enablers in the IoT world. Most of the current cloud-based computing architectures are centralized to handle massive surge of data volume. With edge computing, businesses can access, interact with, utilize data more quickly, in real time. Once the Indonesian IoT infrastructure matures, edge computing will be an effective solution for large corporations and businesses. 

What do you think of this up and coming trend?