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How important is the Internet of Things Analysis (AoT)?
Internet of Things technology can promote production and life and create value for society. In fact, the sensor technology behind the Internet of Things and the data it generates are of greater value, but we pay little attention to them. This situation must be changed!
The importance of Internet of Things analysis
Researchers often put a lot of effort into developing and deploying sensors instead of analyzing the large amounts of data generated by these sensors. However, data that has not been analyzed is worthless. It would be better if the researchers put more effort into the data generated before the streaming sensor was created.
What value will be created if IoT analysis (AoT) is available? Xiaobian is illustrated by several cases:
1. Predictive maintenance
Predictive maintenance is one of the most extensive AoT applications available today. This application analyzes sensor data from equipment such as engines, ATMs, or computers to determine the same pre-failure. In this way, you can take the initiative to solve the problem before the failure occurs.
For example, IBM has helped the US Pratt & Whitney Engine Company achieve predictive maintenance. Through the PMQ (predictive maintenance and quality) predictive model and data integration module, IBM conducts 360-degree health and risk thematic analysis of engine operating conditions and other data, and timely feeds these analysis results to HP, effectively evading the engine. Aircraft accidents caused by failures ensure flight safety.
2, outline the user portrait
Sketching user images has been applied to many companies. The user image provides a unified data service interface for other products of the network to enhance the communication efficiency and enhance the user experience.
Jingdong uses big data technology to outline the user's portrait, and displays the products that meet the user's characteristics and preferences when searching or clicking for different user attribute characteristics, personality characteristics or behavior habits, giving the user a friendly and comfortable purchasing experience. Improving user purchase conversion rate and even repeat purchases can greatly improve user loyalty and user stickiness.
3, real-time positioning
Today's traffic information is very detailed and accurate, and users can receive updated map information in real time. As long as the user's shou machine is connected to the network, traffic information can be obtained in real time even on densely populated roads.
This is because engineers can use a set of data analysis algorithms to convert real-time dynamics such as the vehicle passing rate and vehicle travel speed received by the sensor into intuitive information and transmit it to the user, so that the user can know the road condition in time, thus helping. Users schedule trips more efficiently.
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The value created by IoT data analysis varies by industry:
Through predictive maintenance in the industry, solving problems before problems occur can save a lot of manpower, material resources and financial resources;
In the e-commerce industry, advanced analytical methods often complement the strategy. Product search through user search can win users' welcome and affirmation;
In the clothing, food and shelter related to the public, there is a wide audience. As long as the information provided is convenient for the public, the company will win the trust of the public.
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Internet of Things analysis
Of course, in order to fully realize the potential of AoT, we still need to solve many obstacles. Each of the following obstacles is worthy of a lengthy discussion. The small series is briefly discussed here:
1, the amount of data is too cumbersome
How do we intelligently transfer and retain the content needed for analysis in massive amounts of data? There are two issues to solve here:
One: not all the content delivered by the sensor is valid. It is not easy to screen out the appropriate data in a large number of data. At this time, data filtering technology can be used to filter unnecessary data and cut in the most important data;
Second, too much data is transported, which slows down the delivery. Choosing large-scale investments to restructure the IoT network to bring a wider communication pipeline into the data center, or to do a lot of processing at the edge of the network to alleviate the burden on the central data center is a viable path.
2, the data is too complicated
Regardless of the type or size of the IoT business, the data that needs to be analyzed comes from many different devices. At this time, the dimensions become very large, and a lot of research and testing are needed to determine which dimensions of the data are combined.
It takes a lot of time and effort to organize these confusing data. Using application integration tools is one way to automatically enter data and reduce typographical errors. Careful organization of data is also the key to improving data quality and can lay the groundwork for data analysis.
3. Data security and privacy issues
With the rapid development of the Internet, the network and life are almost integrated, and the collection of data is happening all the time. As long as the data is a little overlooked, it may have a great impact. Especially for enterprises, once the platform data is leaked, it is often very large. Large, need to focus on prevention.
According to a survey conducted by the China National Information Security Evaluation and Certification Center, the threat of information security is mainly due to internal information leakage, which is caused by viruses and hackers. From the perspective of the Internet of Things, the main analysis is the data leakage of hacking types.
The hacker-type data leakage is mainly due to the existence of vulnerabilities in the network zhan or the system, allowing hackers to take advantage of the system and invade the system backend. For example, the well-known Yahoo database sold in the dark network, Yahoo is almost smashed layer by layer, its users have no information security at all.
Here, Xiaobian has compiled some small tips to prevent information leakage:
One: do not use the universal default password
Most compromised IoT devices have vulnerabilities because they have hard-coded default passwords. The developer assigns a generic administrator password to the telnet access or web dashboard, which the user or installer typically does not change. Many people will know the general password, and the user will leave a large number of online records on the Internet. This time, the information leakage has been laid down.
Second: close all ports
Many devices in the IoT botnet have open telnet ports. Open ports allow manufacturers to remotely log in to these devices for device maintenance or to change the underlying operating system. Our advice to IoT manufacturers is: If possible, do not open the incoming port.
Third: build a secure web application
There are many built-in IoT devices for web servers. The server provides a good stand-alone platform for the device: the user can enter the IP address of the printer or security camera to control the status of the device or monitor the device, and does not require the manufacturer to provide continuous cloud services.
Conclusion
With the development of the Internet of Things technology, even if we have been able to cope with the above-mentioned obstacles of Internet of Things analysis, there is still the possibility of unknown vulnerabilities. With this in mind, it is important to build a system when needed to quickly update any software on a web application or IoT device. By giving proper attention during the development phase, IoT devices can find and receive software updates, effectively fixing future errors and keeping devices safe throughout their lifecycle to prevent data leakage.