Smartphones, smartwatches, smart speakers, facial recognition cameras, smart connected vehicles… We live in a world surrounded by smart hardware. The rise of smart cities, smart transportation, smart homes, smart security, smart retail, and smart manufacturing has ushered us into an era of interconnected intelligence, where the boundaries between the digital world and the physical world are gradually blurred.
However, in the world of IoT, how can we manage various types and styles of hardware devices? How can massive streaming data be aggregated and processed in real-time to maintain the latest IoT perception state? How can real-time video stream data be combined with real geographic spatial data to achieve an effect of virtual and real overlay? Zhongdi Digital has launched the MapGIS IoT real-time big data solution, based on domestic GIS software MapGIS, which realizes spatial positioning, device monitoring, spatial tracking, quick querying, visualization display, and business analysis of IoT objects, unlocking a broader application space for IoT with GIS keys.
1. Connecting Data Channels to Aggregate Real-Time IoT Streaming Data
The foundation of the fusion of GIS data and IoT data is connecting data channels. Based on different data acquisition methods, MapGIS IoT real-time big data enhances the capabilities of data gateways, enriches data access protocols and formats, aggregates perception data from various IoT devices, and constructs a real-time dynamic perception data resource system for IoT, which to some extent solves issues like information silos and block segmentation, achieving data interoperability and interconnection among IoT devices.
(1) Accessing General Protocol Data
MapGIS IoT real-time big data supports common standard protocols such as HTTP, TCP, WebSocket, and UDP. Through active pulling or passive receiving, data is accessed in real-time and calculated in standard data formats such as JSON, CSV, and GeoJSON, meeting the needs of conventional real-time data access.
(2) Accessing Video Protocol Data
MapGIS IoT real-time big data supports the RTSP protocol, allowing data from video devices to be accessed, stored, processed, and transcoded in a streaming manner via wired or wireless networks, while integrating geographic spatial information to meet the application needs related to video GIS.
(3) Accessing Sensor Protocol Data
MapGIS IoT real-time big data supports common IoT sensor protocols such as MQTT, CoAP, Modbus, OPC UA, Bluetooth BLE, and CAN. It allows real-time collected temporal and spatial data to be accessed and forwarded based on the standard MQTT protocol, meeting the direct aggregation needs of various sensor data in different industries.
(4) IoT Platform Access
MapGIS IoT real-time big data supports aggregating data collected from various IoT platforms, such as Alibaba and Huawei, through various standard protocols and custom protocols, and can integrate real-time dynamic perception data from multiple IoT platforms on the map.
2. Dynamically Presenting Real Models to Uniformly Control IoT Devices
With the large-scale development of IoT, the types, quantities, and brands of hardware devices in its perception layer are increasing, making effective management of various devices a significant concern. MapGIS IoT real-time big data provides the ability to manage IoT devices, supporting both external and built-in IoT devices. Through the built-in device management module, it uniformly manages various sensor devices in the IoT based on an IoT model, dynamically presenting a real-world model in digital form, and enabling real-time collection, processing, analysis, monitoring, statistics, and early warning of various physical information, satisfying new real-time GIS applications such as digital twins.
3. Processing Real-Time Streaming Data to Perceive the Latest IoT Status
The hardware devices in the IoT perception layer are constantly collecting and generating various data. MapGIS IoT real-time big data, based on Spark Streaming distributed computing technology, provides componentized geographic processing function operators and flexible visualization modeling tools. It supports filtering processors, such as spatial geographic fence filters and attribute filters, as well as basic attribute and spatial processing, such as field mapping, field calculation, buffering, and projection transformation.
In geographic processing, MapGIS IoT enhances complex spatial processing capabilities, supporting 25 types of distributed spatial SQL processing capabilities across three categories: geometric relationship judgment, geometric format conversion, and geometric processing, which can be flexibly combined for use, fully utilizing static data to enhance the dimensions of intelligent perception information and expand application scenarios, such as asset monitoring, diffusion area, and propagation range calculations.
In terms of streaming data output, it provides various output controllers, supporting output to DataStore’s spatiotemporal big data, relational databases, file systems, and other storage engines, allowing for classified storage or file storage archiving management according to time, attributes, etc., while providing data update capabilities to maintain the latest IoT perception state, meeting real-time application needs.
In visualization, MapGIS IoT provides capabilities for temporal data visualization, spatiotemporal data visualization, and real-time analysis visualization, meeting the visualization expression needs of map data and IoT data fusion.
4. Distributing Real-Time Video Streaming Data to Integrate the Virtual and Real Worlds
Video devices are one of the richest sensors in IoT. Due to the low cost of video collection, they are widely used in industries such as smart cities, intelligent transportation, safe cities, smart homes, vehicle networking, and drones. MapGIS IoT real-time big data provides services for accessing, aggregating, storing, transcoding, and distributing web video streams, supporting the mutual conversion of video coordinates and geographic coordinates. By spatializing video data and overlaying it onto map data, it achieves the effect of virtual and real overlay, while also integrating IGServer-S artificial intelligence technology to perform real-time recognition of dynamic targets in the video using geographic information such as time and location, providing technical support for intelligent decision-making and judgment in various application scenarios.
One of the concepts of IoT is to identify, locate, track, monitor, and manage perception objects through perception devices, which inherently requires a geographic information platform to assist in spatial positioning and spatial analysis data visualization. Professionals believe that with the increasing demand for “smart+” applications, the technological integration of BIM + GIS + IoT has become an inevitable trend, and the MapGIS IoT real-time big data solution is a typical representative of this technological integration.
According to the “2020-2021 China IoT Development Annual Report”, the national IoT industry scale has exceeded 1.7 trillion yuan in 2021. Against the backdrop of digital transformation, the empowering role of IoT in the development of the digital economy is becoming increasingly prominent. In response to this development trend, Zhongdi Digital will continue to focus on the independent innovation of key core technologies of domestic GIS, integrating and absorbing emerging technologies, promoting deeper and more diverse application scenarios in the IoT industry, and accelerating the development of digital transformation.
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