Edge computing is one of the newest paradigms of computing where processing and storage are done close to the location, where it needs to be delivered. This eventually has a lot of advantages over the other paradigms of computing, where storage and processing are carried out at distant remote locations which leads to degradation of performance that is caused by latency and low speeds. Even though edge computing also requires a subset of cloud computing for functioning, it is expected that most organizations will move to the edge computing paradigm for offering more value to the users and make the experience of computing better and more effective.
In the future, we will be having 5G, which will literary offer zero latency, and it will also make things easier for multiple devices to communicate with each other with the aid of the internet of things or IoT. The scope of Edge computing is quite large and it all depends upon how the enterprises are taking advantage of edge computing to make their systems run at full potential. So I will talk about the possibilities in the world of technology with the aid of edge computing so that you can have a rough idea of the power edge computing has.
So, without any further delay, let’s get started with the scope and top 8 possibilities of edge computing, and at the same time, I will try to give a clear idea of how it will be better than run off the mill cloud computing technology.
Improved response time in IoT-based systems
Our smartphones and most other devices that rely on machine learning and artificial intelligence to some extent, process the data on the cloud and it is only after that, we get the desired result. For example, if you point your camera toward the photo of a dog, the photo is sent to the servers, and it uses neural networks and existing data to find out what the photo is all about and it is only after that you come to know that it is a dog. Thus, a lot of time is wasted in this process and with the help of edge computing, this problem can be sorted to some extent.
The neural networks or the processing that is carried out in the cloud can be deployed locally on our smartphones and other devices so that the processing can be done instantly and we can get the desired results. After the neural network or the algorithm goes through all the necessary steps to become closest to perfect, it can be deployed locally. Additionally, with modifications to the neural network, the same deployment can also be modified from time to time to make the local neural network and algorithm more accurate. The local edge computing system will also keep learning and that will also update the cloud from time to time, and that will also strengthen the neural networks and algorithms on the cloud.
Improved and more optimized smart cities
The concept of Smart cities is all based on the communication between multiple devices for improved service to mankind and thus, it boils down to communication between multiple cars, traffic signals, and a number of other IoT-connected devices. In the case of smart cities, the transfer of data takes place in real-time and really fast and each of them communicates through the cloud server, which needs to accomplish a number of tasks at the same time. In a number of situations, the central cloud server can get overwhelmed by multiple data transmission and processing at the same time.
With the help of edge computing, this problem can be resolved by deploying storage and processing right on the devices so that, it isn’t necessary for the devices to communicate through the cloud all the time. Additionally, if some quick decisions need to be taken, being depending upon the cloud service can sometimes be ineffective if the cloud server is processing a number of other tasks at the same time. In that case, the outcome will not be effective and the complete concept of smart cities can be shattered. With the aid of edge computing, quick decisions can be taken instantly and that will eventually improve the overall experience and effectiveness of smart cities.
Better health care services and smarter wearables
Wearables are nothing new in today’s world of technology and we all use it more or less. I have discussed several times, how the key behind the most optimized health care services is hidden within the clever use of wearable devices. The wearable devices can send data to the service and those data can be matched with the future outcomes to have an idea of, what are the parameters that are going to change if a patient is heading towards some chronic problem that requires long term treatments or death. The same set of data can also be used to comprehend when the condition of a patient is getting serious.
However, with the aid of cloud computing where the decision is taken by the cloud, there can be some latency in sending the results to the doctor or to the patient directly and that latency can be the time gap between life and death. However, with the aid of edge computing, the decision can be taken by the wearable device itself exactly the same way, edge computing is going to help IoT-based systems. Depending upon the type of problem a patient is suffering from, the possible outcomes can be loaded to the edge computing servers which is the wearable, in this case, to do all the processing locally. This will reduce the unnecessary load on the centralized cloud server.
Better and more functioning virtual assistants
Virtual assistants are hot favourites in the modern era of technology and we all use these fancy little gadgets in our daily lives. Even though virtual assistants seem like magical devices to us, such devices constantly communicate with their servers to give us answers to the questions that we ask. In this process, there is a little latency and that’s where edge computing can be utilized to make the virtual assistants function better than ever. Instead of relying on the centralized cloud servers to give answers to the questions that we ask, edge computing will give the virtual assistants the power to respond on its own without the need to constantly rely on the cloud servers, and that will also reduce the time between asking a question and getting a relevant response.
Implementing the concept of edge computing in the case of virtual assistants will require a lot of data to be kept locally but that isn’t impossible once the concept of edge computing becomes mainstream, and subsequent optimizations are carried out. It is always a matter of fact that edge computing is implemented by bringing processing and storage close to where it needs to be carried out and that’s what will be implemented in the case of virtual assistants. As the virtual assistants will not have to rely on a centralized server, such devices can be made to do a lot of extra work to add more value to our lives.
Better multiplayer gaming with low latency
Gaming is one of the most profitable sectors in the world of Technology, and the implementation of edge computing can also do wonders in this field. Talking about multiplayer games all the players need to connect to a centralized server so that the game can be played successfully between all the participants. Gamers already know, how high latency can ruin the experience of multiplayer gaming, and that’s why edge computing in this field can create breakthroughs. The servers that host the matches in online gaming are always placed at a distant location, typically far away from where the players are located.
As per the laws of Physics, latency becomes the biggest bottleneck that hinders quality multiplayer gaming. With the implementation of edge computing, the servers can be brought as close as possible to where the participants are located geographically, and that should cut down on latency and improve the overall gameplay experience. Implementing multiple servers will require additional cost at the beginning, however, placing the edge computing servers at tactical locations can help the gaming companies deliver better performance without making unnecessary investments.
More advanced quality control in manufacturing
Quality control is one of the most important aspects of manufacturing which adds more value to the sector. Today, quality control is also done digitally and for enhanced quality controls, the photo of the manufactured goods is often sent to the cloud to match the same with an existing photo of the same product and find out whether it is perfect. Additionally, a number of other steps are also carried out in order to ensure that the product has been manufactured free from any kind of defects.
With the aid of edge computing, the quality control process can be made faster as the quality control algorithms can be carried out locally within the production facility. This will ensure your more products are manufactured within a short span of time as quality control, which is one of the most important aspects in manufacturing will be carried out locally. Manufacturing of all shapes and sizes will be positively impacted by the extensive use of edge computing in the years to come. As the supply of goods follows quality control, products will be available faster to mankind.
More optimized and safer autonomous vehicles
We will have to wait for some time till autonomous vehicles gain momentum, but we can find autonomous vehicles going mainstream possibly by the next decade. Autonomous vehicles are complex devices, which need to communicate constantly among themselves to make real-time decisions and drive safely to the destination. The faster the autonomous vehicles can take decisions, the safer it will be for the travellers in that particular vehicle and also those who are on the road. When it comes to making faster decisions, edge computing always offers a great solution and that is also going to be the case for autonomous vehicles.
Collecting data from multiple sensors and uploading them to the centralized cloud servers will require tons of bandwidth and that will eventually overwhelm the servers, which will eventually affect the effectiveness of autonomous vehicles. With the help of advanced edge computing, autonomous vehicles can also take faster and more appropriate decisions with limited onboard resources which is the case with autonomous vehicles. The ability to take a lot of decisions quickly without the need for relying on a centralized server will be of big advantage for autonomous vehicles.
More advanced augmented reality systems
Augmented reality extensively use artificial intelligence to render visual elements on to our mobile screens and with better and more precise rendering, the overall quality and effectiveness of augmented reality-based systems are boosted. With the help of edge computing in augmented reality, the processing can be done locally to carry out the rendering with even lower latency that wasn’t possible, if the rendering needs to be carried out by the remote cloud computing servers. Local rendering will not only decrease the latency but, as the processing will be carried out locally, more functionalities can also be added to the augmented reality systems and that will come in handy for normal users.
The implementation of edge computing in augmented reality systems may lead to errors at the beginning, but when the power of cloud computing and the data in the localized edge computing systems will be fed to the augmented reality system the final results will be more precise. The processed data at the local end will also be synced to the cloud servers and that will eventually make augmented reality systems more accurate and precise for everybody to access across the globe. This two-pronged approach can also be used for virtual assistants, IoT-based systems, and other technologies.
Edge computing will do wonders in all the sectors of Technology, where the overall functionality can be improved by bringing processing and storage closer to where it is needed by the users. I just talked about a few of the most important sectors of technology on which, edge computing will have a positive impact. In the coming days, we can find out more ways to implement the concept of edge computing to make the world of technology more advanced and effective. The data from edge computing systems will also be sent over the servers to the cloud, and that data will also be used by the cloud computing servers to improve the existing technology, neural networks, and other algorithms that are necessary for the proper functioning of the host computer systems.
So, those were the top 8 sectors that will be improved with the implementation of edge computing. Do you know any other sector that will turn more effective with the help of edge computing? Feel free to comment on the same below.