Future Outlook of IoT

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The Internet of Things (IoT) is a dynamic market that is driving change while also helping us cope with it. New applications are emerging every day, and the IoT ecosystem is evolving with it. Let’s explore the key factors driving the IoT in the future and some of the challenges it faces.

Consumer IoT

The consumer sector is one of the largest areas of IoT, which makes everything "smart". Through devices such as smart doorbells, smart locks and smart thermostats, IoT is making our warm homes safer and more efficient. However, although each smart device is very useful, the integration and interaction between them has not been well solved. In the long run, users will eventually be overwhelmed by the supporting applications provided by each device. The future of consumer IoT will include interoperability and integrated management, making it easier to use the large number of IoT devices that will enter our homes in the future.

Commercial IoT

In the future, data provided by the Internet of Things will become one of the main profit points for enterprises. This data helps enterprises understand how customers use products, which in turn can be used to develop new services or improve the efficiency of existing services. For example, enterprises can use video and machine learning to understand the actions taken by customers or predict their results, such as interpreting their expressions when they view products.

IoT Sensors

IoT sensors are a growing area within the IoT. In the past, sensor technology has been dominated by simple hosted sensors that require processing by local computing devices, but in the IoT, smart sensors will become the protagonists, which can automatically collect information and intelligently share information, including sharing information between different smart sensors, in order to reduce errors and improve collection, detection and prediction results.

Vehicle Information System

Telematics, which combines vehicle location, communication and diagnostics with external sensors, is not a new concept. But as the Internet of Things continues to grow, applications for improving driving efficiency and safety are emerging, especially with the application of traffic sensors and machine learning to automotive diagnostics. High-speed communications technologies such as 5G will introduce new features, such as cloud-based entertainment and inter-vehicle communications to optimize traffic flow.

5G

The fifth generation of wireless technology will be an important enabler of new capabilities for the future IoT. Compared to previous technologies, 5G can achieve greater bandwidth, lower latency, and higher device density in a given area. 5G will enable IoT devices to not only communicate effectively with cloud-based resources, but also support data sharing and collaborative processing (using spare computing power or storage capacity), and improve data analysis, thereby achieving real-time optimization of IoT devices.

Machine Learning

Machine learning is a key factor in the development of IoT because the large amount of structured and unstructured data generated by IoT devices cannot be managed under human control. Therefore, data can be collected and streamlined through machine learning algorithms to find its true value. This will be achieved on two levels:

• At a local level, machine learning will be embodied in IoT devices or gateways to provide real-time responses to the data they collect.
• At a global level, machine learning will be applied in the cloud to aggregate data and identify trends or important global details that can benefit both consumers and suppliers.

Large-scale Internet of Things

The emergence of a large number of IoT devices also brings some problems. This situation makes large-scale management and device monitoring very important, and bottlenecks will be created in the process of using IoT to provide data. In this regard, machine learning mentioned above can solve some problems. In addition to machine learning, technologies such as sensor fusion can also reduce the uncertainty of collected data by fusing different sources. Automatic computing can help devices achieve a higher degree of self-management and reduce cloud-level overhead when processing data provided by potentially billions of devices.

Security

Security is both an area of innovation that can do a lot for the future of the Internet of Things, and a problem. This problem includes not only data security, but also access security and overall management security for a large number of potential endpoint devices. One of the more serious problems brought about by the Internet of Things is that a large number of devices share the same software. Once these software have vulnerabilities, attackers only need to do very little to invade a large number of devices and build a botnet. This can only be addressed through device self-management, that is, the device monitors and protects itself when creating updates.