A Info360 site simply requires a web map and a connection to a live database. The following topics guide through the set up of Info360.
This step involves connecting Info360 to a SCADA database (Historian). Info360 will only import specified data from the database and store the data in a local SQL Server database where Info360 builds multiple tables for site performance. For that reason, Info360 can connect to multiple historian databases if necessary while keeping data secure.
Multiple common Database Historians are available for connection to Info360 through standard database connections.
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The Web Map is used to map the locations of sensors and model elements.
Web Maps are typically created by publishing the InfoWater or InfoSWMM model to ArcGIS Online. However, simple shapefiles can also be used for the web map.
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Once Info360 is connected to the SCADA Database, and it has a map of all the sensors with their ID's and locations, then the live data can be mapped in to the Sensor data tables of Info360.
| Field | Description |
|---|---|
| Add New Sensor | Allows you to add and configure new sensors listed below. |
| All Sensors | Allows you to Validate All Sensors or Update All Sensor's WebMap Information. |
| Statistics | Displays the statistics of the various sensors configured in your database. |
| Custom Fields | Allows you to add, edit, and delete custom fields. For more information, refer to How to Manage Custom Fields. |
A separate sensor object is required in Info360 for each feed of measured time series data. Click Add New Sensor to create a new sensor entry, or click on an existing sensor row in the table to view and edit its properties. Basic Configuration
MetadataSensors often record more than just the primary value, and often times this extra data can help to explain what is going on at the sensor. For example, if a flow sensor also includes readings like voltage, batter level, quality of signal, etc., then those time series can be used to investigate unusual flowrate readings from the sensor. To bring in that data, toggle Enable Metadata, and fill out the necessary database mapping to associate the data to the sensor. This data can later be called upon using the MetaData function.
Value MappingValue Mapping is a simple Table Lookup capability that can be used when raw sensor data doesn't give exactly the data you want. For example, if pump status data is recorded as text values of "On" or "Off", it would not be usable in Info360 which requires numerical data (1 or 0). Mapping can easily convert those cases as shown in the example below. Two other cases available in Value Mapping are deciding what to do with missing values and readings of 0 (which in some cases is considered missing). Value mapping can leave those data points as they are, or assign them to be missing value (null), 0, the last known value, or perform a linear interpolation. The checkbox to Continue map missing data up to the latest time is a feature designed for BizBlock and Mass Balance. By default, Info360 will fill in missing gaps during sampling after a new valid data point comes in. It doesn't fill in gaps until then, since the value may get replaced otherwise. For BizBlock and Mass Balance, you may want input values estimated up to the current time based on the last known value; if so then toggle on this option. If you leave it off, the BizBlock and Mass Balance will not use the latest gap-filled data.
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BIlling Data sensors are used in Mass Balance to compare with total calculated usage data for determining the Non Revenue Water. Billing data can be brought in through a database connection in the same format as regular sensor data. Refer to the Individual Sensor setup information above for details on configuring billing data. |
Updatable Sensors use file-based data importing, which updates the data stored for the sensor with each new data push. This approach is well-suited for hydraulic model outputs. Hydraulic models can export model results to a set location accessible to Info360, and then the Data Collector can be set to automatically retrieve the data files and upload to the Updatable Sensor. This data can then be viewed alongside other Sensors as a Reference Chart. Basic ConfigurationThe configuration of updatable sensors is shown below:
Once the Updatable Sensor is created, set up a Data Collector to automatically retrieve data from a set location. Otherwise data can be updated manually.
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Event Data Sensors are used to import time history data of certain events in time that contain information related to the system. This data can later be plotted along side measured data to show how certain events correlate with data in the system. Event data is different from MetaData in that is not associated with a specific sensor. For example, one might want to bring in a history of O&M data or customer complaints, and then plot those points against several sensors in the system to review precursor trends in the data that could predict problems before they happen. This would then be implemented as a Track. Event Sensor data can be accessed on Charts, or by using one of the following Analytical Functions: EventCount, EventData, and EventDuration. Basic ConfigurationEvent Data is brought in as a table with date/time and any number of optional value fields through a mapped Server Configuration above. As shown in the sample below, Event Data Sensors simply require a name, a table from the Server Connection, a Date Field, and any optional fields for plotting values.
The Advanced configuration section provides an optional tag field or where clause to filter which rows of the event table to import. See the Individual sensor set up content above for more information. Value MappingValue Mapping is a standard table lookup capability. Since Info360 expects Event Data to be in a numerical format for plotting, this is often used to convert important text data with values that can be plotted on a chart. See example below to map text values in the data to numeric codes.
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Virtual Sensors can be set up which retrieve live measured data and apply a function expression to produce output at each time step. This opens up a wide range of applications in Info360. Wherever there is a certain calculated result from measured data that is desired for reporting or other analysis, consider setting it up with as a virtual sensor. Later this result time series can be directly retrieved the same way other sensors are viewed. For example, raw pump speed data might come in the form of rotations per minute, however the user would prefer being able to see the nominal speed of the pump. A simple conversion using a function can convert that for the user. Basic ConfigurationThe Basic Configuration is for defining the standard sensor properties including Type, ID, Alias, Interval, and Units. Refer to the Sensor fields above for descriptions. This tab also defines the analytical function expression used for the virtual sensor. Expressions can access a library functions in Info360 including the ability to call data from other sensors. Refer to the Analytical Functions page for setting up expressions.
Value MappingValue Mapping is a standard table lookup capability which can be applied to the final output of the function. For virtual sensors the value mapping is different from normal sensor value mapping in that it applies unique outputs for ranges in function output.
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It can be tedious to add all sensors manually. Typically for new sites, it is best practice to configure all of the sensor data mapping in excel, and then use CSV to bulk import to Info360. Contact us for assistance setting up the CSV file. |
Tank volumes in Info360 are calculated from Tank Level sensors and Tank geometry. Tank geometry can be defined as cylindrical with a constant set diameter, or using curve data. Curve data is input as a table of tank volumes for each level reading. Info360 applies linear interpolation on the table to determine the volume at any measured level.
The Tank Curve Manager is used to save tank curves which can later be referenced by tank level sensors.
Tank Curves can be entered manually or imported from CSV.
Once the data is mapped for each sensor, it can be loaded into the Info360 database through sampling at the specified interval.
Setting the maximum sampling intervals defines a limit to how far back historical data will be sampled.
It can be a good idea to first test sample a few intervals, and later sample all desired data.
Once set up and sampled, sensors will continue to retrieve new live data from the SCADA database and store all sampled data in the Info360 database.
The logic map below shows the decisions and logic Info360 uses while bringing in data from SCADA.
See the Data Sampling page for more information on how SCADA data is sampled and stored in the Info360 database.
icons to create, edit, and delete Connections.
icon and browse to a zipped set of shapefiles.
, to populate the composite layer service address and sensor ID Field.
to add additional Map Services.
