The new-generation devices are becoming more efficacious and powerful with each passing day. They are massively helping in reducing data centre loads and are complementing cloud capabilities to obtain exciting & groundbreaking IoT applications. While countless of today’s always-connected tech devices reap seamless benefits of cloud computing, IoT (Internet of Things) manufacturers, as well as the app developers, are beginning to explore the advantages of doing more analytics & compute on the devices themselves- what we essentially know as Edge Computing.
The on-device approach helps in reducing the latency for critical apps, lessen cloud dependence, and effectively manage the enormous deluge of data being generated by the IoT. In this post, I will help you understand how Edge computing is facilitating the realm of the Internet of Things, but before we actually start, let’s start with the basics.
What is Edge Computing?
Edge Computing is essentially a process to develop analytics and compute on the device itself. Simply put, the ability to do on-device advanced processing and analytics is known as edge computing. For a better understanding, think of “edge” as the galaxy of internet-connected devices inclusive of the gateways sitting on the field- that is, the counterpart to the “cloud”. Edge Computing enables new possibilities to IoT applications, specifically for those banking on machine learning for performing tasks such as face recognition, obstacle avoidance, object detection, and language processing.
Why Edge Computing?
The on-device approach greatly helps to:
- Reduce latency for critical apps
- Seamless management of the massive deluge of data that are generated by the IoT
- Less dependence on cloud
- It can assist in reducing connectivity costs by sending only useful information rather than transferring the raw streams of sensor data. Extremely crucial for devices that connect through LTE/Cellular like asset trackers or smart meters.
Criticality Of Edge Computing For IoT
The emergence of edge computing is an iteration of a prominent technology cycle that starts with centralized processing which then transforms into more distributed architectures. Nonetheless, the mobile revolution got hugely accelerated when smartphones replaced feature phones at the edge of the eminent cellular network. Well, if we take a thorough glance, edge computing will also have a similar effect on the Internet of Things, thereby, powering a potent ecosystem growth as end devices become capable of running complex applications and turn more powerful.
Following a similar trend, some OEMs are also devising IP camera that uses on-device vision processing to distinguish family members, watch for motion, and send alerts only when an individual is not recognized or doesn’t fulfil the pre-defined parameters. By operating computer vision tasks within the camera, the company lowers the amount of cloud storage, cloud processing, and total bandwidth used versus the choice of sending raw streams of video across the network.
Privacy and security can also be enhanced with edge computing by retaining sensitive data within the device. Processing at the edge also lowers latency and helps in making the connected apps more robust and responsive. Some other use cases include autonomous vehicle, drone, AR, remote monitoring of oil & gas, and healthcare.
All in all, the edge devices are regularly being devised with increased computing capabilities. With the combination of superior connectivity technologies such as 5G will help in delivering faster and massive connectivity. What are your thoughts on Edge Computing and IoT? Let us know by dropping your thoughts in the comment section below.