Today most everything that exists or moves on the planet (and above and below it) is measured in real time. Most of the sensor data streaming from this web is georeferenced, meaning it can be consumed, organized, summarized, and analyzed by a GIS. It’s such a big idea, it has its own buzzword: the Internet of Things.
A vast amount of data is created every day from sensors and devices: GPS devices on vehicles, objects, and people; sensors monitoring the environment; live video feeds; speed sensors in roadways; social media feeds; and more, all connected through the Internet. What this Internet of Things means is that we have an emerging source of valuable data. It’s called “real-time” data. Only recently has the technology emerged to enable this real-time data to be incorporated into GIS applications.
The real-time GIS capabilities of the ArcGIS platform have transformed how information is utilized during any given situation. Real-time dashboards fed by the IOT provide actionable views into the daily operations of organizations, empowering decision-makers and stakeholders with the latest information they need to drive current and future ideas and strategies. Dashboards answer questions such as: What’s happening right now? Where is it happening? Who is affected? What assets are available? Where are my people?
Real-time data is as current as the data source that is updating it, whether that data is being updated every second, minute, hour, or daily. What is real time to one organization might not be real time to another, depending on the type of scenario being monitored.
Real time is a concept that typically refers to the awareness of events at the same rate or at the same time as they unfold (without significant delay). It’s often confused with frequency, or the intervals between events, which is essentially how often the event is updated. The update interval, or frequency, relates to the term “temporal resolution,” which can vary from one application to another.
For example, most aircraft monitoring systems provide two updates every second, whereas it may take every hour to provide a weather update. For monitoring their networks, energy utilities use systems, also known as SCADA (Supervisory Control and Data Acquisition), that sample data about voltage, flow, pressure, and more from analog devices at very high frequencies (e.g., 50 hertz). This can result in high resource requirements for network bandwidth, system memory, and storage volume.
The data that fueled geographic applications in the past was created to represent the state of something at a specific point in time: data captured for what has happened, or what is happening, or what will happen. Although this GIS data is valuable for countless GIS applications and analyses, today the current snapshot of what is happening now falls out of sync very quickly with the real world, in many cases becoming outdated almost as soon as it is created.
Real-time GIS can be characterized as a continuous stream of events flowing from IoT sensors or data feeds. Each event represents the latest measured state, including position, temperature, concentration, pressure, voltage, water level, altitude, speed, distance, and directional information flowing from a sensor.
Maps provide the most basic frameworks for viewing, monitoring, and responding to real-time data feeds.
A utility organization may want to visually represent the live status of its network with information that is captured by sensors in the field. Although the sensors on the network are not physically moving, their status and the information they send changes rapidly. Radio-frequency identification (RFID) is being used in a wide variety of environments to keep track of items of interest. Warehouses and logistics companies use RFID to track and monitor inventory levels. Hospitals use it to track equipment to make sure it has gone through proper cleansing procedures before being used.
A wide range of real-time data is accessible today. Connectors exist for many common devices and sensors enabling easy integration between the IoT and your GIS.
The Internet of Things is taking shape all around us. Large investments are being put into smart cities, autonomous vehicles, public safety services, utilities, and telecommunication infrastructure. The sensors that are being implemented are effectively digitizing our planet to a level we have never seen before. The sheer number of sensors, the abundant variety of sensor types available, and the frequency of updates that these sensors produce is a new opportunity for GIS communities to leverage the integration of Real-Time GIS and the IoT.
In many ways, the evolution of Real-Time GIS has been driven by IoT. Early systems focused primarily on automatic vehicle location and mobile asset monitoring. This has continued to develop and evolve as new types of sensors have become available and have dropped in cost.
Today, Real-Time GIS systems strongly complement IoT solutions by expanding capabilities to incorporate continuous space–time analysis. Autonomous vehicles are a good example in which vehicles report locations as well as observations about road conditions. These collective observations can be used in concert to analyze road conditions, and provide hazard alerts and alternative routing when required. The ability to combine information from multiple sensor types and locations is critical to managing complex operations.
This integration of different sensor networks is combined intelligently in a geospatial framework to optimize operation and is one of the biggest values of IoT. Previously disparate sets of information can be brought together, in real time, to see all facets of a problem and make smarter decisions, thus improving efficiency, optimizing services, and reducing costs. And using a geospatial context is vital for this to be successful.
Geography is a natural integrator, and GIS systems play an important role in integrating the relationships between different sensor systems. The interaction between data streams and corresponding action are all essential in building smarter applications using real-time geoanalytics.
Real-time dashboards are created by adding “widgets” to an operation view. Operation views are easy to set up and configure. The map widget creates the primary map display and serves as the source of data for other widgets. You choose which data source or attribute value is displayed by the widget, specify the appearance settings, enter a description or explanatory text, and set any other properties required for the particular widget.
Widgets are used to represent your real-time data in a visual way. For example, a symbol could represent the location of a feature on a map; a text description could be displayed in a list; and a numerical value could be shown as a bar chart, gauge, or indicator.
Widgets are used to represent your real-time data in a visual way. For example, a symbol could represent the location of a feature on a map; a text description could be displayed in a list; and a numerical value could be shown as a bar chart, gauge, or indicator.
Each operational view is updated with the latest data by setting a refresh interval on both the widget and each layer.
ArcGIS® GeoEvent Server for ArcGIS® Enterprise is a GIS server extension that brings your real-time data to life, allowing you to connect to virtually any type of streaming data, process and analyze that data, and send updates and alerts when specified conditions occur, all in real time.
With GeoEvent Server, your everyday GIS applications become frontline decision applications, helping you respond faster with increased awareness whenever and wherever change occurs.
GeoEvent Server is capable of receiving and interpreting real-time data from virtually any source. The system understands how the real-time data is being received as well as how the data is formatted. Input Connectors (shown here) allow you to acquire real-time data from a variety of sources.
Output Connectors are responsible for preparing and sending the processed data to a consumer in an expected format. An Output Connector translates its events into a format capable of being sent over a particular communication channel.
GeoEvent services enable you to define the flow of the event data as well as to add any filtering and processing on the data as it flows to the Output Connector. Applying real-time analytics allows you to discover and focus on the most interesting and important events, locations, and thresholds for your operations.
With Operations Dashboard, you can create real-time dashboards that allow you to visualize and display key information about your operations. These operational views can be stored in ArcGIS and shared with individual members of your organization, with groups within your organization, and publicly with anyone using ArcGIS.
In many cases, data streamed into ArcGIS in real time will be captured in a geodatabase. To support historical archiving of events, a best practice is to use a historical or temporal feature class to store all the events received from the data. This allows the state of each object to be stored indefinitely, everything from the first event received until the present. As you can imagine, the size of this data can grow to be quite large, especially over an extended period of time. The growth rate of your data is largely dependent on the message size and the frequency of the incoming data. A best practice is to define and enforce a retention policy for how much history is actively maintained in the geodatabase.
Real-time data takes on many different forms and has many different applications. Some of these examples link to live-feed maps and some to the item descriptions for the feeds themselves.
National Hurricane Center data describes the current and forecast paths of tropical activity
The Current Wind Conditions layer is created from hourly data provided from NOAA.
Minute-by-minute earthquake data for the last 90 days comes from the USGS and contributing networks.
LA Metro’s Realtime API gives access to the positions of Metro vehicles on their routes in real time.
These stream gauge feeds allow users to map current water levels to monitor flood and drought risk.
Updated every five minutes, this dynamic map service monitors traffic speeds and incidents.
North Carolina established the North Carolina Floodplain Mapping Program (NCFMP) to better identify, communicate, and manage risks from flood hazards within the state in response to the devastating flooding caused by Hurricane Floyd in 1999. This led to the establishment of the Flood Inundation Mapping and Alert Network (FIMAN) to provide real-time flood information throughout the state.
In the first week of October 2015, the system was put to the test through the combination of Hurricane Joaquin passing to the east and a stalled low-pressure system that produced historic rainfall totals and subsequent flooding in portions of the Carolinas. The storm, which had rainfall totals ranging from three inches to more than 20 inches over a three-day period, resulted in more than 20 fatalities and damages estimated in the billions of dollars.
Although North Carolina was spared the extreme rainfall experienced in South Carolina, the storm still resulted in significant flooding along the coast and eastern counties. FIMAN was used by the State Emergency Operations Center throughout the storm to monitor flooding conditions, assess potential impacts of flooding on the basis of weather forecasts, and target the deployment of emergency response personnel and resources. FIMAN served as an invaluable tool in communicating risk to public officials and the public.
Operations Dashboard for ArcGIS is a Windows app that you can download and run locally or a web-based version that runs in a browser. It’s where you design your operational views.
There are many principles to consider when configuring real-time dashboards:
Operations Dashboard for ArcGIS provides two kinds of operations views:
This extends ArcGIS Enterprise and provides capabilities for consuming real-time data feeds from a variety of sources, continuously processes and analyzes that data in real time, and updates and alerts your stakeholders when specified conditions occur.
Learn more about GeoEvent ServerWhen snowstorms hit, they can paralyze transportation systems in an instant, bringing local government operations to a standstill and preventing citizens from moving around the city. To quickly clear its roads of snow, a city's fleet of snowplows must be managed efficiently. Furthermore, to prevent traffic accidents and streamline transportation, the populace must be kept informed about which roads are safe to use and which aren't.
To help a city in Utah with its snowplow problem, you've been tasked with creating two real-time, easy-to-use apps that track the location of snowplows throughout the city and the accessibility of roads in the wake of a snowstorm. One app will be for government officials, and must provide additional information about vehicles and road status in order to streamline the plowing efforts after a storm. The other app will be for the public in order to keep citizens informed about the situation in the city. First, you'll build a web map in ArcGIS Online that contains real-time data about snowplows in the city. For the government officials, you'll create an operation view in Operations Dashboard for ArcGIS that combines your map with lists, charts, and other helpful information. For the citizens, you'll create a web app with Web AppBuilder that clearly and simply communicates the key information about roads and snowplows. While both of your final outputs will contain real-time data, each will be tailored to the specific needs of the intended users.
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