Big Data: The Best Technological Usage in Traffic Management

Have you ever thought of the capacities and restraints of big data? Sometimes, it may tempt you to think about how big data can do anything and everything. With the help of big data, you can observe the current situation as well as predict the situations which are likely to occur.

Big Data tools and techniques can capture images and video data continuously. Big data tools and technologies aid the traffic department currently retrieves a terabyte of data every month. The increasing amount of traffic data now poses challenges in the city’s ability to effectively manage traffic with the help of Iot traffic management

Challenges:

  • It enables centralized management of traffic data. Centralize access to image and video traffic data stored in the data centers of different divisions. Centralize access to traffic management facilities, equipment and application systems. 
  • Big Data optimizes the utilization of massive data. Store vehicle monitoring data for as long as possible to give information support for departments such as public security, a criminal investigation, and economic investigation and front-line police.
  • Additionally, it improves traffic flow across the city. Enhance dispatch capability for dealing with various kinds of emergencies and accurately forecast traffic patterns. 

Solutions:

  • Deploy a unified data center based on Intel Xeon processor E5 series. You can also deploy 22 servers running on Intel Xeon processor E5 series and 198-terabyte storage space for centralized storage for the digital traffic information. 
  • Use the Hadoop Distributed File System (HDFS) and Apache HBase* to provide permanent storage and seamless expansion of vehicle and traffic violation image data accumulated in the past 24 months. Use Hadoop to retrieve data in real-time.
  • Set up the Trustway key vehicle dynamic supervision system. Taking advantage of the open platform for analytics from Intel, deploy Trustway system for massive-scale data mining and analysis. 

Technical Results:

  • Enhanced storage capacity for large data. Apache Hadoop provided a mass data storage solution with high fault tolerance and throughput, allowing reliable storage for massive information and seamless expansion capacity. 
  • Achieved powerful I/O processing function. The Intel Xeon processor E5 series enhances I/O processing. Now a single server can allow synchronous transmission of a 500KB picture with an average speed of 250 times per second or asynchronous concurrent storage of 2,000 times. 
  • Provided high-performance HBase database. Apache Hadoop enabled complex data queries in the vehicle monitoring system. 
  • Now it takes only seconds to search for plate numbers correctly or the vehicle’s driving record from huge data.

Improves Business Value:

  • It improves traffic case detection ability. Within 24 months of traffic violation picture data stored in the system will enable the traffic police departments to retrieve data.
  • It also improves traffic police supervision of the motor vehicles. Plate numbers and driving history of a passing vehicle can easily be tracked by the Traffic police.
  • It also provides easy access to relevant vehicle analysis data. It takes only 10 seconds to investigate complex traffic inquires.

Big Data and IoT: Go Hand in Hand Traffic Management

All of us hate traffic jams, isn’t it? The assimilation of big data with IoT cloud platform within a network of sensors and vehicles means traffic management is becoming more smarter and efficient.   

The idea of big data and IoT implies the traffic quantity which should be permitted at a particular time interval can be controlled. With the application of smart devices, real-time information can be gathered easily.

Ending Note:

Experts want to find out the patterns in traffic conditions viz. Intersections and roundabouts. Thus allowing computers to assist actively in searching dangerous situations or driver’s change in driving behavior. 

Big data will make our lives easier by integrating local traffic patterns giving a coherent view. Thus allowing the planners to make the best decisions in the near future.