This part will walk you through the different public datasets that we publish from our live field demonstrations.

Our public dataset is called demo. Tables available are hvac, power, vehicle_tracker & weather. Our project name is dw-open-001. For information about adding our project to your BigQuery project browser see https://cloud.google.com/bigquery/bigquery-browser-tool#browseprojects

Vehicle Tracking

We have installed tracking units that plug into a vehicle's OBD-II port and enable the collection of interesting data from vehicles on the road. The deviceWISE Cloud blends this data from other sources, such as geocoding, comparing with the speed limit, etc. The data is available here: dw-open-001:demo.vehicle_tracker

BigQuery Schema

Field Data Type Description

thing

 STRING Unique identifier for the tracker.
ts TIMESTAMP Timestamp for the record.
prop_fuelecon FLOAT Fuel economy measured in miles per gallon.
prop_fuellevel FLOAT Fuel tank level as a percentage.
prop_odometer FLOAT Virtual odometer.
prop_rpm FLOAT RPMs.
prop_speed FLOAT Speed in miles per hour.
prop_speed_limit_delta FLOAT Difference between current speed and speed limit in miles per hour.
prop_tripmiles FLOAT Miles driven in the past trip.
attr_fueltank STRING Size of the fuel tank in gallons.
attr_vin STRING VIN of the car being tracked.
attr_phoneno STRING Phone number for publishing alerts.
loc_lat FLOAT Latitude.
loc_lng FLOAT Longitude.
loc_heading FLOAT Heading in degrees.
loc_speed FLOAT Speed in miles per hour.
loc_corrId STRING Correlation ID used for associating records.
loc_streetNumber STRING Street number.
loc_street STRING Street name.
loc_city STRING City.
loc_state STRING State.
loc_zipCode STRING ZipCode.
loc_country STRING Country.

Home Power Monitoring

We have installed current transducers in the breaker box of a home to monitor the power usage within a single family home. The data is available here: dw-open-001:demo.power

BigQuery Schema

Field Data Type Description

thing

 STRING Unique identifier for the tracker.
ts TIMESTAMP Timestamp for the record.
prop_waterheater FLOAT Watts used by the water heater.
prop_hvac FLOAT Watts used by the air conditioner (heating & cooling).
prop_main FLOAT Watts used by the entire house.
prop_office FLOAT Watts used in the office.
prop_other FLOAT Watts used everything not sub-metered.
prop_refrigerator FLOAT Watts used by the refrigerator.
loc_lat FLOAT Latitude.
loc_lng FLOAT Longitude.
loc_heading FLOAT Heading in degrees.
loc_speed FLOAT Speed in miles per hour.
loc_corrId STRING Correlation ID used for associating records.
loc_streetNumber STRING Street number.
loc_street STRING Street name.
loc_city STRING City.
loc_state STRING State.
loc_zipCode STRING ZipCode.
loc_country STRING Country.

Home HVAC System

We monitor 3 rooms in a single-story single family home in Boca Raton, FL. The data is available here: dw-open-001:demo.hvac

BigQuery Schema

Field Data Type Description

thing

 STRING Unique identifier for the tracker.
ts TIMESTAMP Timestamp for the record.
prop_brhum FLOAT Bedroom relative humidity rh%.
prop_brlight FLOAT Bedroom ambient light in lumens.
prop_brtemp FLOAT Bedroom temperature in degrees Fahrenheit.
prop_lrhum FLOAT Living room relative humidity rh%.
prop_lrlight FLOAT Living room ambient light in lumens.
prop_lrtemp FLOAT Living room temperature in degrees Fahrenheit.
prop_offhum FLOAT Office relative humidity rh%.
prop_offlight FLOAT Office ambient light in lumens.
prop_offtemp FLOAT Office temperature in degrees Fahrenheit.
loc_lat FLOAT Latitude.
loc_lng FLOAT Longitude.
loc_heading FLOAT Heading in degrees.
loc_speed FLOAT Speed in miles per hour.
loc_corrId STRING Correlation ID used for associating records.
loc_streetNumber STRING Street number.
loc_street STRING Street name.
loc_city STRING City.
loc_state STRING State.
loc_zipCode STRING ZipCode.
loc_country STRING Country.

Querying our dataset

To query our public tables you can use the project name, dataset name and table name. For example:

SELECT COUNT(*) FROM [dw-open-001:demo.hvac];

You have completed this guide

That completes this guide, demonstrating the powerful features available to collect data from the Internet of Things, filter and process that data as required, and publish the appropriate data from the deviceWISE Cloud to Google Cloud Platform where it can be processed using GCP's full set of tools and capabilities.

Continue onto What's next for additional resources to continue learning about the platform.