IoT Knowledge Hierarchy and Technology Challenges

The Internet of Things (IoT) is thought to be the next phase in the evolution of the Internet. The combination of the Internet with wireless communications and embedded wireless sensor networks, according to the European Commission, will enable a paradigm shift in transforming our daily gadgets into intelligent and context-aware ones in the future years. 

It has found a place in practically every aspect of human existence, which can be inescapable, due to its technological frameworks, market shares, values, and revenue.

It is also expected that, in the not-too-distant future, the Internet will be integrated into a variety of things, such as clothing, toothbrushes, and food packaging, with context awareness and pseudo-intelligence on processing capability among connected things; also, efficient use of limited available power necessitates new forms of ­communication between things and people as a result. 

The knowledge hierarchy depicts how raw data is turned into actionable intelligence and then used to aid decision-making in the context of the Internet of Things. 

  • Raw sensory data may be considered of as the bottom layer in the knowledge hierarchy process, where a vast quantity of data is collected from numerous IoT devices in terms of Exabyte (EB) or even more as time goes on. 
  • The following layer preprocesses the raw data to provide structured, filtered, and machine-readable data that may be processed to acquire the information. 
  • The third layer supplies us with knowledge by revealing hidden information from structured data, allowing us to take intelligent action at the conclusion of the process. 

IoT Technology Challenges 

  • As the Internet of Items strives to link all of the things in a single network and create a vast quantity of data for actionable information, it faces a number of obstacles. A few of these are mentioned farther down. Integration of data from a variety of sources. 
  • The data collected from numerous sources, such as sensors, social networking feeds, and mobile devices, is all in distinct contexts; hence, integrating these forms of data is a challenge, but one that, if done well, may offer a lot of value to decision-making. Scalability is an important factor. 
  • Dealing with the volume, diversity, velocity, and veracity of data generated by IoT presents a challenge for real-time operations to efficiently manage the data and perform meaningful analysis. Management of devices. 
  • Even if a significant number of devices are networked (not all) with servers over a wide region and can successfully exchange data, controlling a device that is not linked to the network but is nevertheless involved in the data transmission process may face certain data connecting challenges in an IoT scenario. 
  • Diverse Devices Making IoT devices work together is a difficulty since many firms design their products in various ways and use various standards. Flexibility is a virtue. An IoT scenario should be created in such a way that new devices and technological advancements may be accommodated without too much difficulty.

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