How to analyze the data of Internet of Things

Internet data analysis is discussed too much, but for the analysis of Internet of Things data, it is too little. In this paper, the author will start from classifying the data of the Internet of Things, and tell us how to analyze the data of the Internet of Things.

How to analyze the data of Internet of Things

After checking on the internet, there are many articles about Internet data and business data analysis, but the articles about Internet of things data analysis can hardly be found. Therefore, a special article on Internet of things data analysis has sprouted, which serves as a replica of my work experience and methodology. At the same time, I hope it can inspire all children's shoes.

I. Introduction

Friends of "Deep Analysis of How to Build the Service Structure of the Internet of Things" should know more clearly: How does the service of the Internet of Things work? What are the elements? What role does each part play? How does it work? What are the key technologies or skills?

From sensors - > devices - > gateways - > servers, the whole path can well achieve the data acquisition to the Internet of Things platform, but why do we analyze these data, how to apply these data, how to do data analysis?

1. What is Internet of Things Data?

Based on the construction of the Internet of Things service, we can know that the data of the Internet of Things mainly refers to the data sent by sensors and equipment. Part of the data is the acquisition value of the real environment parameters, part is the conventional information value of the equipment, such as: status, fault information, error code, operation and so on.

Internet of Things (IOT) data will generate data under any circumstances, and new data will not emerge without human participation. The amount of data is much larger than the business data of traditional business systems

If we simply classify the data of the Internet of Things according to the change of data, we can divide it into static data and dynamic data.

1) Static data

Data of attributes of sensors or devices will not change with time or increase with time without adding new devices. The representative data are device ID, device address and so on, which are stored in structured and relational databases.

2) Dynamic data

It refers to the data that will change with the time period. Each data has a corresponding relationship with the time value. The data is stored in a sequential manner. The amount of data is very large, and the more frequent the data is collected, the larger the amount of data is.

It will not only increase with the increase of the number of equipment, but also increase with the increase of time. Usually, such data will be deleted at a certain time, otherwise the amount of data will be too large. According to the requirements of some industries, usually the preservation period is set at 3 to 5 years. There are no specific requirements. The key is to set the requirements of the industry.

2. Why do I do data analysis on the Internet of Things?

If the Internet of Things is only responsible for collecting data from a bunch of sensors and equipment, it is just a bunch of huge data gathered together, which can not produce practical value.

However, in practice, we can find that the data of the Internet of Things is very interesting. After analysis, we can use sensor or equipment data to clearly understand the operation of the equipment and the trend of the real environment operation, and help to make predictions and respond in advance.

For example, the use of Internet of Things data can effectively predict mechanical failure, reduce the work delays caused by equipment failure. According to the change of equipment status information value uploaded by equipment and the parameters collected by specific sensors, the probability of failure can be monitored and predicted, and the response can be made in advance. In this way, an Internet of Things service can be raised from a simple data acquisition to a service level that can continuously create added value.

At the same time, the operation based on the collected data analysis can also rebuild the new operation mode of enterprises. Some contents can refer to my other article "How Internet of Things Technology Helps Enterprises to Transform and Upgrade". On the whole, the application of Internet of Things data analysis in the new form will greatly help enterprises to transform and upgrade.

3. What aspects of Internet of Things data can be used

What applications can Internet of Things data help us to do? In summary, there may be the following:

Monitoring: By visualizing the data of the Internet of Things directly, we can monitor the status of the equipment and know what happened in time.

Counter-control: When abnormal data need to be intervened, it can directly inform the corresponding administrator, remote control equipment to achieve counter-control, improve operational efficiency, and avoid direct access to the equipment site.

Statement statistics: Based on the data of the Internet of Things, we can make statistical analysis of relevant historical data according to actual needs, and present it to different types of users in the form of graphs or graphics according to different dimensions, so as to help them quickly and intuitively know the operation of the equipment.

Prediction/Prediction: Based on the data analysis model, some events can be predicted, and the probability can be obtained in advance, so as to respond in time, avoid causing greater losses, or directly obtain other benefits.

Artificial Intelligence: When data and experience accumulate to a certain extent, the system can automatically respond to event data analysis, without manual intervention.

Based on this, we basically gave you a basic groundwork. So next, we will share the focus of this time, let's see: how to conduct data analysis of the Internet of Things, what are there?

Please read the Chinese version for details.