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How to deal with big data in the solution of the Internet of things? aiming at this problem, this article introduces the corresponding analysis and answer in detail, hoping to help more partners who want to solve this problem to find a more simple and feasible way.

With the evolution and development of the Internet of things, all conceivable things (or things) and industries will become more intelligent: smart home and smart city, smart manufacturing machinery, smart cars, smart health and so on. Countless things authorized to collect and exchange data are forming a whole new network-the Internet of things-a network of physical objects that can collect data, transfer data, and complete user tasks in the cloud.

The Internet of things and big data are on the road to victory. However, there are still some challenges and problems that need to be addressed in order to benefit from this innovation. In this article, we are pleased to share with you the knowledge we have accumulated in the field of Internet of things consulting over the years.

How to apply big data to the Internet of things

First of all, there are many ways to benefit from big data of the Internet of things: in some cases, rapid analysis is sufficient, while some valuable insights can only be obtained after in-depth data processing.

(1) Real-time monitoring. Data collected through networking devices can be used for real-time operations: measuring the temperature of the home or office, tracking physical activity (counting steps, monitoring exercise), etc.; real-time monitoring is widely used in health care (for example, obtaining heart rate, measuring blood pressure, sugar, etc.); it has also been successfully used in manufacturing (for controlling production equipment), agriculture (for monitoring cattle and crops) and other industries.

(2) data analysis. When dealing with big data generated by the Internet of things, we have the opportunity to go beyond monitoring and gain valuable insights from these data: identifying trends, revealing invisible patterns, and finding hidden information and relevance.

3) process control and optimization. Data from the sensor provides additional contextual information to reveal important issues that affect performance and optimize the process.

Traffic management: track traffic loads at different dates and times to develop recommendations for traffic optimization, such as increasing the number of buses at a specific time period to see if there is any improvement, and to recommend the introduction of new traffic light schemes and the construction of new roads to reduce traffic congestion on the streets.

Retail: track the sales of goods in supermarket shelves and inform the staff to replenish the goods before they are almost sold out.

Agriculture: according to sensor data, water crops if necessary.

Predictive maintenance. Data collected through networking devices can be a reliable source for predicting risks and proactively identifying potentially hazardous conditions, such as:

Health care: monitor patients' health status and identify risks (for example, which patients are at risk of diabetes and heart attack) so that timely action can be taken.

Manufacturing: predict equipment failures so that they can be resolved in time before they occur.

Not all Internet of things solutions require big data. It should also be noted that not all Internet of things solutions require big data (for example, if a smart home owner wants to turn off the lights with the help of a smartphone, he can do so without big data). It is important to consider reducing the workload of processing dynamic data and avoiding storing large amounts of data that are not useful in the future.

Big data Challenge in the Internet of things

Unless a large amount of data is processed to gain valuable insights, the data are completely useless. In addition, there are challenges in data collection, processing and storage.

Data reliability. Although big data will never be 100% accurate, before analyzing the data, it is important to make sure that the sensor is working properly and that the data used for analysis is reliable and will not be damaged by various factors (for example, the adverse environment in which the machine is running, sensor failure).

What data to store. Networked devices generate terabytes of data, so it is a difficult task to choose which data to store and which to delete. More importantly, the value of some data is far from being shown, but you may need it in the future. If you decide to store data for the future, the challenge is to do so at minimal cost.

Depth of analysis. Once not all big data is important, another challenge arises: when rapid analysis is sufficient and when more in-depth analysis is needed to bring more value.

It's clear. There is no doubt that networking in various fields can make our lives better, but at the same time, data security has also become a very important issue. Cyber criminals can hack into data centers and equipment, connect to transportation systems, power plants, factories, and steal personal data from telecom operators. Big data of the Internet of things is a relatively new phenomenon for security experts, and the lack of relevant experience will increase security risks.

Big data's treatment in the solution of the Internet of things

In the Internet of things system, the data processing components of the Internet of things architecture vary according to the characteristics of the input data, the expected results and so on. We have developed some ways to deal with big data in the Internet of things solution.

The data comes from sensors connected to things. "things" can be any object: ovens, cars, airplanes, buildings, industrial machinery, rehabilitation equipment, etc. The data can be periodic or streaming. The latter is essential for real-time data processing and rapid management of things.

Things send data to the gateway for initial data filtering and preprocessing, thereby reducing the amount of data transferred to the next Internet of things system.

Edge analysis. Before in-depth data analysis, it is necessary to filter and preprocess the data to select the most relevant data needed for some tasks. In addition, this phase ensures real-time analysis to quickly identify useful patterns previously discovered in the cloud through in-depth analysis.

Cloud gateways are required for basic protocol conversion and communication between different data protocols. It also supports data compression and secure data transmission between the on-site gateway and the central Internet of things server.

The data generated by the networking device is stored in the data lake in its natural format. The original data enters the data lake through "flow". The data is kept in the data lake until it can be used for business purposes. The cleaned structured data is stored in the data warehouse.

The machine learning module generates a model based on the previously accumulated historical data. These models are updated regularly (for example, once a month) with new data streams. The input data is accumulated and applied to training and creating new models. (source IoT Home Network) when these models have been tested and approved by experts, control applications can use them to send commands or alerts in response to new sensor data.

Summary

The Internet of things produces a large amount of data, which can be used for real-time monitoring, analysis, process optimization and predictive maintenance. It should be remembered, however, that it is not easy to gain valuable insights from vast amounts of data in a variety of formats: you need to ensure that the sensor works properly and that the data is safely transmitted and processed effectively. In addition, there is always a question of which data is worth storing and processing.

Despite some challenges and problems, it should be remembered that the Internet of things has a strong momentum and can help companies in many industries to open up new digital opportunities.

The answer to the question about how big data deals with the Internet of things solution is shared here. I hope the above content can be of some help to you. If you still have a lot of doubts to be solved, you can follow the industry information channel for more related knowledge.

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