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Internet of Everything (IoE) is the fastest growing technological trend in the today’s world. Broader then the concept of the Internet of Things (IoT), IoE not only means connecting devices and people to the Internet but also providing smart and knowledge-based services. The future technology will be completely dominated on IoE, it will be “all around us and reside within the background of our lives”.
IoE stands on three pillars: billions of everyday objects which have to be made smart, information-centric networks, and providing smart and knowledge-based services through real-time analysis of collected data. IoE is one of the most promising future technologies, for it integrates the daily life with technology, making everything smart and artificially intelligent.
IoE is the advancement of technologies like the Internet of Things, Artificial Intelligence, Machine Learning etc., and integrating them together. The systems won’t only provide services, but will self-learn to gain knowledge, will analyze the situation and provide a solution based on that. But each component to reach IoE has its own difficulties and limitations, which have to be dealt with.
The first pillar of IoE consists of millions of everyday objects which have to be connected to the Internet. From industrial machines, electrical appliances, to wearables, packaging technologies, medical appliances etc. all are being integrated to the net. At present, traditional silicon chips are then used to connect devices, but to really become ubiquitous, electronics have to be shaped in such a way that it can be integrated with all type of objects – miniature sized, soft, flexible and wearable.
Recent developments in Printed Electronics are paving the way towards low-cost and low-performance electronics. It defines a technology for creating electronics on some substrate using organic and inorganic inks. It gives the possibility of preparing stacks of micro-structured layers and thus, thin-film devices.
Many Packaging companies are using Printed Electronics for developing smart labels, for Anti-Counterfeiting Packaging techniques. Especially, pharmaceuticals, healthcare, beauty products, appliances, and food and beverage companies are increasingly using this technology, which improves security as well as is disposable.
The concept of System in Package (SiP) has led to miniaturized and more powerful systems, where various components are stacked on top of another, to create thin but highly robust electronics.
The present Internet is built on Internet Protocol (IP) based technology, where point-to-point communication takes place on the basis of IP addresses of source and destination. But with billions of smart objects connected to the Internet, there will be a burst of data flowing through the net in the coming years, which the present technology will not be able to handle. Also, information-based search on a search engine is the entirely different thing from searching for sensor data from smart objects.
For this, Information-centric Network is being developed which makes data content directly addressable and routable, also known as the Content-centric network (CCN) or Named-data networking. In the security model of CCN, individual pieces of data are made secure using encryption, instead of using additional layers for security features. When requested by name, CCN delivers named content to the user from the nearest cache, therefore less number of network hops are traversed, redundant requests are eliminated, and overall fewer resources are consumed.
After connecting different devices to the net and making the network suitable for IoE, the real use is when these devices generate real-time insights and take action accordingly. Developments in the fields of Machine Learning, Deep Learning, Artificial Intelligence, Big Data, Cloud etc. have made possible efficient and secure processing of vast amounts of data to provide low-power and smart services. But the objective is not only to make these devices smart but also capable of self-learning so that they can use their previous experiences to generate more accurate and better solutions and services.
Self Learning Mechanism shows the proposed architecture for self-learning and knowledge enhancement. It contains three modules:
1) The data collection module collects real-time data and processes it using the previous knowledge and training. Then the data is forwarded to Machine Learning Module (MLM).
2) Using machine learning model from Knowledge Processing Module (KPM), the learning process is initiated. If it satisfies the standards set by the designer, the learning result and parameters are transferred to KPM for generating knowledge. If the learning results aren’t up to the standards, re-learning process is initiated under different learning conditions.
3) After updating knowledge, this new knowledge is used to process the future inputs.
Thus, the IoE concept stands on three pillars: Smart devices, Information-based Networks, and self-learning devices for smart and real-time services.
But to implement it possesses a number of challenges, both in hardware and software parts. For IoE applications, flexible, miniaturized, very low-power, low-cost and extremely fast chips have to be designed. Many difficulties are arising: like downscaling CMOS technology for miniaturization has led to compromised amplifier performance. Designing techniques for chips with self-learning algorithms, without compromising with its speed, size, and at low costs, have to be explored.
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