IoT is predicted as the new future for the technical world. As more people realize the benefits of mobile applications and internet connectivity, developers are building towards a world where we will be able to control all of the simple functions of a household with just an app, from turning on the gas stove to switching off the lights. This is not just a big leap in the web world, but also a striking change in all the fields as this would govern the future.
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In Gartner's view, nearly seventy-five per cent of the global organizations will use containerized apps till 2022. Container technology is not a new concept and has been a part of Traditional enterprise IT environments and cloud architecture. The recent developments in the IoT industry have contributed to the growth of container technology by increasing the demand for supplier-neutral IoT technologies.
The environment of virtualization is lightweight and comprises a whole runtime. Container technologies are helpful as they help us underline the difference between OS and underlying infrastructure. This is the reason they are seen in IoT platforms as to help you connect to any device and make almost any legacy machine or piece of IoT-ready equipment.
Security is the matter which concerns the tech world today and the worries would keep on increasing. To deal with the ever-increasing concerns, IoT would concentrate on security matters. IT administrators have grown hostile to know the number of gadgets connected to their network, leaving them susceptible to attacks. The previous decade has seen an exponential rise in the number of gadgets connected to the internet and this trend would keep an upward trajectory. Hence, all the more reason for maintaining caution.
Strengthening AI-enabled processes at the edge
Containers are also empowering edge computing as they are becoming a vital part of AI-enabled processes at the edge. Both AI models and machine learning models can be trained and put to work on edge devices along with individual containers. However, the software has to be updated regularly. IoT platforms have made it possible for containerized cloud workloads to be managed and processed without any technical barriers.
AI meets IoT
Not just the concerns of security are taken care of but an improvisation to production procedures has also been made. To put it simply, the process has been streamlined as "Artificial IoT" reduces deviation from the optimum in the process of manufacturing, hence, enabling high performance at marginal costs and reduced wastage. Through AI, the process of production can be optimized regularly with the assistance of ML methods. Apart from this, AI-driven analytical solutions have the control to agglomerate huge amounts of sufficiently high-quality data and information; process it quickly, and deliver effectual insights. The assimilation of AI, Big Data, and IoT devices would effectively contribute to protecting us against security risks. This would see more compliance in the coming decade.
Developers till now, have focused mainly on security improvement along with innovation. They usually commit code, release, and update addictions. But their role is ever-evolving as individual contributions come to the surface. Some features offered by the IoT platforms such as the IoT app store, allow developers to present their work and get feedback from fellow developers. Developers can easily access the IoT app from the IoT platform on marketplaces. The IoT platform would help the developers to easily develop their apps while making it easy for the users to discover the most relevant app. Hence, making it easy for the users to get relevant apps on their devices.
A greater role for IoT
The mobile app development industry is about to experience a frenzy in IoT. So diversification of mobile app development trends in the coming years on a larger scale is expected.
IoT apps for predictive maintenance in smartphones
The IoT or "Internet of things" is connecting more and more devices to the internet. This connectivity allows for rapid exchange of data between these objects, and in turn, makes it possible to predict when a device would fail. Predictive maintenance apps are already proving their authenticity and relevance in industrial manufacturing. Now, these apps are joining us as consumers at a greater pace. It provides predictive maintenance solutions for your individual needs and is an additional resource that any consumer should consider as they make a purchase going forward.
Countless technologies are coming in the field of AI and Big data, for example, machine learning, neural networks, and convolutional neural networks. The strategies of Big data of capturing and storing IoT data, plus apps for processing the humongous amount of data collected by IoT devices, will further be gaining more attention. The machine learning models which are packaged as IoT apps are to be rolled out at the IoT edge and are gaining popularity. The amalgamation of Big data, IoT, and AI help developers simplify the tasks and assists industrial manufacturers, automotive, retail, and logistics companies in enhancing their operations and reducing the workload. Hence, helping them to improve their services.
IoT apps for anomaly detection in Industrial Manufacturing
Industrial manufacturing would also be strengthening its data analytics capabilities to improve its anomaly detection techniques. The ML algorithms would be packaged as IoT apps and launched in manufacturing plants all around the world. With this, manufacturers would be able to trace and anticipate unwanted behaviour in their operations and possible anomalies in equipment performance to correct these from anywhere. IoT apps have made it possible to track asset conditions in any part of the world from sitting at one location. Thus, streamlining the efforts of the manufacturer. This, in itself, has made the future of IoT a certainty and a big step in technological advancement. The world of AI and IoT would see a lot of changes in the coming decade and this would mean an overall advancement in every sphere.