As an important part of the Internet of things, the name of the Internet of vehicles is more and more mentioned by the media. However, do you really understand the Internet of vehicles? The Internet of vehicles is just a lot of Internet of vehicles? No! In addition to the literal meaning of the Internet of vehicles, the Internet of vehicles and big data are inextricably linked.
In our life, we are not lack of data, but lack of equipment and technology to collect data. For example, our car is a big data source. When the car starts, the speed, tire pressure, car temperature, real-time road conditions and other data flows are constantly changing. When the whole city or even the whole country's vehicle network is connected, the data uploaded by each car will contain the location status information of the car. After the data is associated with the database of the traffic management department, these data will also contain the owner of the car After tens of millions of vehicles are connected to the Internet, it is easy to generate massive data.
The core value of big data analysis is prediction. The more complete the data, the less parameters, and the more accurate the prediction. In the field of Internet of vehicles, the data source is huge, but the parameters that need to be predicted are not many (much less than the weather forecast), so the prediction of big data can play a very effective role.
1. Route planning and traffic warning
The traditional way for drivers to understand the road conditions is to listen to the radio, but this way is very inaccurate and not timely, because the general congestion will not be broadcast, and it will be broadcast through the way of news, at least more than an hour ago. Now the location of the incident is not blocked, the drivers still don't know.
The Internet of vehicles system can collect the driving data of all Internet connected vehicles. After big data analysis, it can get the real-time congestion and road conditions of almost every road section, and make reasonable route planning for users. According to the user's personal driving habits, the system will also intelligently analyze the mistakes that the user may make and the road sections that are prone to problems during driving, and timely send a reminder to the user to maximize the driving safety factor.
2. Resource allocation of bus public transportation system
The normal operation of the public bus transportation system is an important condition for a city to be orderly, but the planning of bus transportation routes, the distribution of vehicles and the arrangement of time are difficult problems, because the distribution of passengers traffic at each station in each period of time is statistical data, which needs a large number of long-term data for calculation and analysis, so as to get accurate results. This kind of statistical data is just in line with big data Characteristics of the analysis. Reamol bus video passenger counting sensors is the excellent choice to offer accurate passenger traffic data and onboard passenger numbers, the passenger traffic distribution will help bus choose the best route to save time and resource.
According to the distribution of passenger flow at each station in different time periods, the public transport company can initially plan the number of vehicles and the length of the route, and then make a reasonable allocation according to the actual vehicles and human resources, so as to solve the three major problems of the least vehicle demand, the shortest driving route and the least driver working time.