HELIOS PointXplorer Big Data platform

Entering the era of big data, as one of the main sources of massive data, the application of various technologies in security industry has produced huge data. Moreover, these data are becoming important strategic resources at the enterprise, social and national levels. In the future, security industry is a typical data-dependent industry, relying on data to speak. The fusion of security and big data is mainly embodied in Storage, Observation and Usage. Supported by big data, the storage model of data captured can be stored in a distributed data storage system in an efficient, safe and inexpensive way, and the data can be queried, retrieved and located accurately by big data technology. In the data application level, through the structured association of each system, we can quickly search all the information of the event, so as to achieve the practical application of the data. Through Helios big data architecture platform, we can improve the performance and maintainability of product functions.

Main targets of the big data platform: are referring to achieve configuration management of external hardware devices, access and storage of external data, and call and analysis applications of stored data.

Main contents: through the large data storage system, the data of each subsystem can be effectively correlated, the data captured by the front end can be collected, and the unstructured data can be processed quickly with the cloud computing system, the structured data can be extracted quickly, and the data mining and application can be strengthened.

Helios® PointXplore™ Indoor Real-Time Positioning & Identification Big Data System mainly consists of two parts logically:

Fast and simple to deploy, HELIOS® iLOCALIZER Close-Proximity Cellular Sensor sit alongside the existing network without consuming valuable network connection resource, and with no need for complex network management and integration.

HELIOS® iLOCALIZER Close-Proximity Cellular Sensor do not connect into the core network but are designed to seamlessly capture critical user information and location data within a closely targeted area, including location, dwell time, IMSI (Even IMEI and MSISDN in 2G mode) and range – to support Data Monetization and Safe Cities applications, even allow government agencies or security, surveillance and border protection teams to send SMS alarm message to specific handsets in its coverage area.

Unlike common indoor location-based systems with only Wi-Fi or Bluetooth, which require users to turn on, opt-in and download an app, HELIOS® iLOCALIZER 2G/3G/4G Cellular Sensor mainly use the cellular network protocol to capture information from passing handsets – automatically, securely, and with no user intervention required. Built-in ideal high capacity rechargeable Li-ion battery inside the iLOCALIZER or external UPS enables keeping continuous working during sudden power outage time.

The PointXplorer™ RTPIS Big Data Center mainly responsible access, storage, computing, exchange and management for 24/7 data capturing from remote Cellular Sensors, as well smart big data analysis functions, such as personnel location view, personnel activity trajectory, crowd monitoring heatmaps and etc.

The PointXplorer™ RTPIS Big Data Center is composed of 4 elements as below:

PointXplorer™ Security Load Balancer

PointXplorer™ Security Load Balancer

PointXplorer™ Big Data Warehouse

PointXplorer™ NMS

Helios Big Data Center architecture is divided into three layers, such as Application Layer (Business Layer), Middle Layer (Data Layer) and Hardware Layer (Device Layer) as below figure:

Application Layer (Business Layer)

It is mainly based on various applications of data acquisition. Business layer does not need to process and analyze data. It only needs to obtain the processed data from the middle layer of the platform through query interface and display it on the interface.

Middle Layer (Data Layer)

The middle data layer includes data access services, data storage services, data computing services (including real-time and offline computing), operation monitoring services and platform management services.

Hardware Layer (Device Layer)

Using X86 universal server, no expensive computer equipment and high-end storage equipment need to be purchased, which greatly reduces the hardware cost.

Firstly, all Cellular Sensor devices are deployed remotely in the indoor location and coverage area. The remote Cellular Sensor devices will collect the mobile phone signature (IMSI) of passing handsets in its coverage area. The collected data can be sent back to HELIOS® PointXplorer™ RTPIS Big Data Center by wireless or fix line way. The HELIOS® PointXplorer™ RTPIS Big Data Center receives and processes the data and stores it in the corresponding storage engine. The application can access the corresponding data through the data exchange interface. The system data processing process is as follows:

The captured mobile phone signature (IMSI) data are sent back by the remote Cellular Sensor device, and the reported data are first processed by LVS Load Balancing Server (Linux Virtual Server), then sent to the gateway.

The Gateway decode and parses the data according to the protocol and sends the parsed data to Kafka, then Kafka will store it in a Topic defined as Raw Data.

Real-time Computing Task (Process) reads data from the Raw Data Topic and sends it to the RawData Parsing Module after data cleaning.

The Raw Data Parsing Module sends the parsed data to the Kafka, then Kafka will store it in a Topic defined as Parsed Data, and then sends the data to the Data Judgment Module.

The Data Judgment Module judges according to the existing rules and sends the judgment results to the Alert Data Topic in Kafka and the Current Status Module respectively.

The Current Status Module judges the status of the remote Cellular Sensor device and updates it to Redis database (Hadoop Database) if the state changes.

Data Import Module imports data from Kafka into HB database and HDFS (Hadoop Distributed File System) in an asynchronous way.

Offline Computing will periodically read data from HDFS for various report analysis and data mining.

Business Application Layer can call data from Data Warehouse through Data Exchange Interface.

  • ZooKeeper: A distributed, open source distributed application coordination service. It is a software that provides consistent services for distributed applications. It provides functions such as configuration maintenance, domain name service, distributed synchronization, group service, etc.
  • Kafka is a high throughput distributed publish-subscribe messaging system that can handle all the action flow data in a consumer-scale website.
  • Hadoop: A distributed file system, HDFS for short, is highly fault-tolerant and designed to be deployed on low-cost hardware. It also provides high throughput to access application data and is suitable for applications with very large data sets.
  • MySQL: A relational database management system that stores data in different tables rather than in a large warehouse, increasing speed and flexibility.
  • Spring: An open source design-level framework that addresses the loosely coupled issues of business logic and other layers, so it runs through the whole system application with the idea of Interface-oriented programming.
  • MyBatis: An excellent persistence framework that supports SQL queries, stored procedures, and advanced mappings. MyBatis eliminates almost all manual settings of JDBC code and parameters, as well as retrieval of result sets.

HELIOS® PointXplorer™ RTPIS Big Data Center not only collects data based on the two dimensions of mobile phone signature (IMSI) and the working position of the HELIOS® iLOCALIZER™ Cellular Sensors. On the basis of having massive data, the data mining, cluster analysis, quick retrieval and other data processing technologies are adopted to realize that HELIOS® PointXplorer™ RTPIS Big Data Center enable to offer users the basic big data analysis functions of different angles and directions.

HELIOS® PointXplorer™ RTPIS Big Data Center can provide users with basic data analysis. The Big Data system can merge, analyze and correlate massive collected data, and finally present the data value to customers in a simple and clear chart form.

Customers can manipulate or view various data information from HELIOS® PointXplorer™ RTPIS Data Warehouse through Web pages, such as:

  • Data acquisition and display
  • Real-time positioning of personnel
  • Personnel History Track Query
  • Historical Records Query
  • Indoor crowd analysis (Heatmaps)
  • Conditional Filtering Query (Personnel filtering by Time and Location Conditions)
  • Early warning function (early warning of entry of specific personnel, early warning of crowd, early warning of intrusion into specific areas)
  • Statistical Report Form (Statistics of Collection Quantity)
  • Active Personnel Statistics (according to the frequency of mobile phone signatures)
  • Various customized statistic reports available based on customer’s requirement