Car networking in the era of big data

With the continuous development of the Internet, big data is becoming an upsurge, and the discussion of big data in the industry has reached an unprecedented peak . As a result of the emergence of mobile internet, car networking is a big issue whether it is the access of vehicles, the selection of service content, or the accuracy of services.

Each set of data uploaded by the vehicle carries location information and time, and it is easy to form massive data. On the one hand, if the characteristics of big data are complete and mixed, the characteristics of big data related to car networking and car are complete and accurate. For example, some data related to the vehicle itself has a clear ID. According to this ID, it can be linked to the corresponding owner information, and this information is still accurate.

On the other hand, we can see that the characteristics of big data, such as the consumer habits and hobbies of the Internet of Car and the driver, are complete and partially accurate. Therefore, it is more meaningful to study the big data of the car networking.

The definition and characteristics of big data

Big data, or huge data, refers to the huge amount of data involved that cannot be accessed through the current mainstream software tools. It can be retrieved, managed, processed, and organized in a reasonable time to help the company make business decisions. More active information.

We can see from the definition of authority that there are four characteristics of big data: the volume of data is huge. Jump from TB level to PB level; data types are numerous. Web logs, videos, pictures, geolocation information, etc. mentioned. , Low value density, high commercial value. Take video as an example. The data that may be useful during continuous and continuous monitoring is only one or two seconds. Processing speed. 1 second law.

Car networking big data can be used to predict the extreme. For example, predict traffic jams, real-time traffic information, active safety, bus schedules. Driver driving behavior analysis.

The core of big data is prediction, which is very useful in the car networking industry. For example, big data is needed for forecasting traffic flow. Regarding traffic flow, our simulation system now pays more attention to traffic flow and congestion, and in the era of big data, we no longer care about the causality, and we attach importance to correlation, that is, we do not analyze the cause of congestion, but it is a certain period of time. A section of the road will be congested. It is also possible to analyze the interests of riders based on the big data of the Internet of Vehicles.

Big data has been used in the commercial vehicle field, such as the operation of shift management in the public transportation field, floating car data in the taxi field, and logistics in the logistics industry.

How to solve the three major problems faced by public transport companies: the least equipped capacity, the shortest distance between vehicles, and the least time for drivers? How to analyze the distribution of passengers at different time periods and sites? How to achieve safe and intelligent operation and operation schedule? In the public transportation industry, the above problems are ubiquitous,

Through the big data of the Internet of Vehicles, these problems in the bus industry can be solved. According to various time periods, such as the size of passenger flow at each site, the number of operational vehicles equipped on the line, and the line is equipped with drivers, line lengths, vehicle operating speed, and other big data, the number of vehicles allocated at each time slot of a line and the departure interval can be determined. It solves three problems: the least capacity, the shortest running distance of the vehicle, and the driver's working time.

Based on traffic flow, holidays, weather, climate, natural disasters, road accidents, historical data, ticketing methods, residential community construction, and other conditions, a planning model is established to quickly reflect these factors that affect the operation plan. . For example, increase lines, increase vehicles, increase drivers, and effectively formulate bus operations plans. At the same time, it can accurately manage the operation scheduling, can automatically schedule through big data, optimize the driving operation plan, and quickly adjust and optimize the operation circuit.

Since the emergence of the rookie network company, the concept of large logistics has finally been mentioned by the industry. What is “big logistics?” refers to the company’s own logistics system (consisting of fleets, warehouses, personnel, etc.) and the sharing of distribution information and resources of third-party logistics companies so that they can make full use of all resources and reduce total logistics. Expenditure, lower operating costs.

At present, with the expansion of business, the number of vehicles in the logistics industry is increasing, and there are many models. Many companies still use manual methods for vehicle management. The workload is large. Statistical analysis of vehicle operation data is difficult. Statistical results lag behind, which is not conducive to the company's decision-making management. At the same time, the whole process of monitoring is not performed during vehicle operation. Personnel's violations of laws and regulations cannot be promptly alerted, nor can they react promptly to the help of the staff.

How to improve the status quo of logistics enterprises that are relatively backward in management, and meet the requirements of “high service quality, strict on-time rate, minimal cargo loss rate, and low logistics costs” of shippers?

How to solve the logistics industry's operational information feedback delay, high operating costs, the high-altitude driving rate of freight vehicles, drivers cheat to the safety of goods and vehicles bring great hidden dangers?

How to quickly and efficiently provide users with reliable logistics services?

How to maximize the utilization of transportation resources to improve overall business operation efficiency?

These are the imminent problems in the current logistics industry.

For the above problems, the car networking technology can solve the urgent problems of the car owners. Through the transparent management of the transport process, the car can be dispatched rationally. According to the big data of the car's driving, the unblocked route of the car's driving line can be predicted and a safe and smooth plan can be planned. Travel routes to reduce waiting time on the road due to traffic.

Through the big data of vehicle operation, fuel consumption of the same route can be quickly analyzed, advance warnings of accident-prone road sections can be calculated, and calculations of vehicle trips can be accurately analyzed. The informationization level of the company can be improved, and the status information and goods of the goods can be known at any time. The entire process of arriving at the destination ensures the transparent management of the transportation process, enabling the company's operational management intelligence, service punctuality, and predictability.

At the same time, through the big data of the vehicle operation, real-time road conditions of high-speed, national, and provincial roads can be obtained. At the same time, analysis of drivers’ driving laws provides reference data for the selection of gas stations, service stations, and service stations.

On the other hand, a large part of the cost of logistics is storage costs. Through the vehicle networking technology, the massive data is analyzed and calculated. After reasonable scheduling, the empty driving rate of the vehicle is reduced, and each moving truck can be used as a floating storage space, which improves the turnover rate of the storage space and helps the enterprise. Reduce storage costs.

Thinking about big data

The era of big data affects our thinking. In the past, our understanding of the travel process, the traditional concept only focused on providing customers with navigation and entertainment, and did not conduct an in-depth analysis of this process. During this process, respectively before going on the road, after parking. For this process, we can extend the service content of a lot of car networking, and each stage can not be separated from the acquaintance society, each stage will generate big data, big data can extend many value-added services.

The accuracy of service content If rely solely on the power of service providers, then service providers will have to invest huge human or capital and have to go through a long period of time. Obviously this approach is not feasible. The ideal way to solve this problem is through the interaction of the owner and the community website. Only in this way can the relevant points of interest be collected quickly. This must be big data analysis.

For customer information, whether it is a depot or an automobile dealer, it is considered as the lifeblood. What is the fact? The fact is that at this stage, these customer information are not used at all, can some value-added services be extended from these customer information? . To put it bluntly, this information can't bring "Customer Lifetime Value". The customer's lifetime value refers to the total income that each buyer may bring to the company in the future.

Like a product, customers’ contribution to corporate profits can also be divided into the lead-in period, rapid growth period, maturity period, and recession period. Obviously, at this stage, the product form or the enterprise's informatization level is limited. On the one hand, it is unable to complete the excavation of big data. On the other hand, it lacks specialized analytical tools, and the car networking era gives us unlimited imagination and makes everything possible. It is possible!

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