In 2019, we are watching an even deeper penetration of the Internet of Things into our daily lives. It might seem to you that this term has recently become less common – this is a sign that the phenomenon is moving from a ‘hype’ state to an ‘ordinary’ state. We can say with confidence that in the near future, most of the devices that we use – cars, televisions, watches, kitchen appliances – will all be connected to the network and will be able to interact with each other.
The same thing happens in production: machines and robots are becoming smarter and also connected to the network, generating data, working with which increases efficiency and opens the way to implementing approaches such as predictive maintenance. In total, it is predicted that by the end of 2019 the number of connected ‘things’ around the world will reach about 26 billion. Below are five IOT Trend 2019 which tell us about how this will happen over the next 12 months, and how we will get used to the fact that the Internet is not only what we connect our computers and smartphones to, but almost everything we can imagine.
According to Forrester research, the main role in the rapid growth of IOT Development Services is assigned to business: 85% of companies are already introducing or are planning to implement Internet of Things this year. The Internet of Things brings a whole host of benefits to business. Over the previous years, we have already seen several successful experiments, for example, special devices have appeared in the retail trade that interact with buyers’ smartphones and allow you to display detailed information about the product on their screens. However, the locomotive for IoT implementation is the manufacturing sector.
Here, during 2019, more and more enterprises will see a benefit in connecting equipment to the network, which will allow obtaining data on the state and performance parameters of almost every detail and exchange these data with other devices. Forecast-based preventative maintenance of equipment has long been predicted by technology evangelists, but it is currently only implemented by the largest companies that have invested heavily in IoT for several years. But their experience increases the understanding of how useful and beneficial such solutions can be, therefore it is expected that smaller organizations will also take these technologies into their arsenal, being confident that investments will definitely pay for themselves.
Related: – Largest IOT Rules IN 2019
Just like the regular Internet has given us a voice, IoT will give a voice to all the devices that we use. We are gradually getting used to using voice control by assistants like Amazon’s Alexa or Siri’s Apple. But 2019 will be the year when all our other devices will find their own voice interface: almost every automaker is working on its own voice assistant to help drivers more conveniently and safely drive. Voice control with natural voice feedback should also be available for industrial and corporate technologies. Voice control makes sense in many situations because it allows you to leave your hands free to perform those operations that still require them, and also removes part of the burden from our eyes, which can now focus on more important things.
This method of communication with the machine also removes a number of barriers to interaction. Initially, mankind used computer code to transmit commands to devices, then user interfaces, graphical environments, and other tools appeared that reduced barriers to entry. Voice recognition and generation is the logical next step towards creating technologies that everyone can use to work more efficiently or improve their lives.
Edge computing – technologies and algorithms that differ in that the calculations are done as close as possible to the place of data collection, for example in sensors or cameras. The thing is that the huge amount of data collected by such devices is completely useless. A good example is a camera, which in normal mode will transfer terabytes of data to the server, while at least some megabytes of these records, demonstrating suspicious activity, may turn out to be of any use.
If such devices are able to carry out primary processing of data in a certain way instead of thoughtlessly transferring them to the cloud, data transmission networks will be much less loaded with useless traffic and much more computing power will be occupied by really useful calculations. In the above example, image recognition algorithms running on the firmware of the camera itself will be able to independently analyze frames for suspicious activity and will only transmit potentially useful data to the server for further processing and storage.
Artificial intelligence (AI, AI) and the Internet of Things (IoT) are pretty closely related. IoT contributes to the incredible amount of new data that will appear as a result of its development. When hundreds and thousands of machines interact with each other in the production network, analyzing large arrays of data obtained with this, you can get results that the human mind could never get, especially at the same time, often critical for making a decision.
Training machine learning algorithms to identify various deviations in these data will allow you to see opportunities to increase efficiency or prevent upcoming problems in the early stages. As the size and complexity of IoT networks increases, they will become increasingly dependent on new developments in machine learning and AI. This is also important in terms of IoT security, There are additional opportunities for automated threat detection.
This year we will see the launch of the first fifth-generation consumer networks that can operate up to 20 times faster than existing mobile data networks. IoT depends on the speed and availability of data services, and today there are still places that smart technologies have not yet reached just because of the lack of high-quality communication. With the help of mobile networks, which will become faster and more stable than wired counterparts, the scope of IoT projects can expand significantly. Ideas such as Smart City, where the entire urban infrastructure is integrated into a common network and all data are processed to improve the urban environment, are becoming more viable. The technology used by self-driving cars will also benefit significantly from increased throughput.
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