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  • ITS Washington 2019 Logo

Moonshadow and DB4IoT at the ITS Washington Annual Conference

By |December 3rd, 2019|

Moonshadow’s Anita Van Asperdt gave a presentation on December 3, 2019 as part of a panel at the ITS Washington Annual Conference and Exhibition at the University of Washington in Seattle. The panel session was titled “Vehicle Electrification – What’s it got to do with ITS?” and included fellow panelists:

Mike Usen, DKS Associates
Michael Ippoliti, HDR
Edward Smalley, Seattle City Light

Van Asperdt’s presentation focused on “EV-Charging Infrastructure, Siting and Place Design.” […]

  • Code Orange featured image

Arcadis Code Orange

By |October 24th, 2019|

Arcadis, a global design, engineering and consulting company, kicked off the first Code Orange, a data analytics hackathon, in North America last week! Focused on hacking mobility in Los Angeles, Arcadis brought together data scientists, mobility experts and partners including Moonshadow to create and present data-driven prototype solutions in four intensely collaborative days, October 18-21.

Wander Boesjes (East Coast Sales Engineer) represented Moonshadow at the event and worked closely with several of the Code Orange teams as they leveraged the power of Moonshadow’s DB4IoT with INRIX Trips analytics platform during the […]

  • INRIX Webinar - DB4IoT with INRIX Trip Paths & Trip Reports 2018.0618

DB4IoT and INRIX Trip Paths – Webinar Presentation

By |June 19th, 2019|

INRIX  just announced the availability of a powerful new solution for understanding the movement of people through the trips they take – INRIX Trip Paths. The DB4IoT mobility analytics platform is terrific for deploying the INRIX Trips Paths data for transportation analysis.

INRIX Trip Paths is billions of GPS data points transmitted by moving vehicles or devices expertly map-matched by INRIX to road segment data from sources like OpenStreetMap. It is actual observed individual trips, including associated entry and exit times for each segment of road.

INRIX teamed with Moonshadow and the […]

  • Introducing the O-D CO2 Matrix

Introducing the O/D CO2 Matrix Using Connected Vehicle Data to Reduce Greenhouse Gas Emissions

By |June 10th, 2019|

On June 5th at ITS America in Washington DC, Moonshadow CEO, Eimar Boesjes, delivered a presentation titled “Introducing the O/D CO2 Matrix Using Connected Vehicle Data to Reduce Greenhouse Gas Emissions” at a technical session and panel discussion.

Millions of connected vehicles generate detailed movement data. After anonymizing the data it can be used to gain insight into the movement patterns of vehicles as well as which movements generate the most greenhouse gas (GHG) emissions.

Anonymized connected vehicle data includes the origin, destination and waypoints of trips. Timestamps give us the day […]

  • The histogram shows the distribution by time of day.

NYC Motor Vehicle Collisions Data in DB4IoT

By |April 10th, 2019|

The NYC Open Data portal provides an interesting data set from the NYPD that is a breakdown of every motor vehicle collision in NYC by location and injury. Each record represents a collision in NYC by city, borough, precinct and cross street. This data can be used by the public to see how dangerous/safe intersections are in NYC.

We imported the data into the DB4IoT analytics platform to visualize the six-year period from July 2012 through June 2018. The following series of images detail the results. Public data sets such as […]

  • ITS-WA-Presentation

ITS Washington Annual Meeting Presentation – Using Connected Vehicle Data to Estimate Greenhouse Gas Emissions

By |December 19th, 2018|

Eimar Boesjes, Moonshadow CEO, delivered a technical presentation at the ITS Washington annual meeting on December 11th, 2018 in Seattle.

Estimating vehicle emissions from connected vehicle data does not replace existing environmental models, roadside emissions measurements or environmental models. Rather, it augments these. We think it would be extremely interesting to compare the emissions estimates from DB4IoT with INRIX Trips with actual measurements from roadside air quality measurements, with emissions calculations from gasoline sales and with the existing environmental models. These different approaches each give a different insight and they can […]