Moonshadow and DB4IoT at the ITS Washington Annual Conference

By |2021-07-15T00:07:58+00:00December 3, 2019|DB4IoT News, DB4IoT with INRIX Trips, DB4IoT with Wejo Events, The Internet of Moving Things, Uncategorized|

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 AssociatesMichael Ippoliti, HDREdward Smalley, Seattle City LightVan Asperdt's presentation focused on "EV-Charging Infrastructure, Siting and Place Design."  View the presentation here.

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Arcadis Code Orange

By |2021-06-30T23:25:13+00:00October 24, 2019|DB4IoT News, DB4IoT Transportation Data for GHG Reporting, DB4IoT with INRIX Trips, The Internet of Moving Things, Uncategorized|

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 [...]

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DB4IoT – Create Freeway On-Ramp to Off-Ramp Origin-Destination Matrices

By |2021-07-15T17:42:04+00:00October 8, 2019|DB4IoT News, DB4IoT with INRIX Trips, The Internet of Moving Things|

In this DB4IoT Mobility Analytics Platform use-case video we’ll demonstrate how to create freeway, on-ramp to off-ramp, origin-destination matrices. You'll also learn how to define freeway filter networks and how to analyze traffic that is avoiding a freeway because of congestion.

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DB4IoT – Introducing a Network of Pass Through Gates

By |2021-07-15T17:41:15+00:00July 18, 2019|DB4IoT News, DB4IoT with INRIX Trips, The Internet of Moving Things|

We've added some exciting new features to empower engineers, planners and agencies to easily create networks of pass-through gates in the DB4IoT interactive mobility analytics platform. These networks can be as simple or complex as necessary to answer the specific questions at hand for your detailed analysis. Watch the following video for an overview.

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Moonshadow Launches DB4IoT Transportation Data for GHG Reporting

By |2021-06-30T23:47:22+00:00June 11, 2019|DB4IoT News, DB4IoT Transportation Data for GHG Reporting, DB4IoT with INRIX Trips, The Internet of Moving Things|

DB4IoT Transportation Data for GHG Reporting from Moonshadow provides detailed insight into the travel activity patterns in cities, metro areas and counties and can be used by consultants and local governments to gain a deeper understanding of when and where transportation is generating the most emissions. DB4IoT Transportation Data for GHG Reporting delivers maps and spreadsheets that can be included in Community GHG Inventory Reports, Climate Action Plans and Transportation Plans that consultants prepare for cities, counties, MPOs and DOTs or can be used by local governments themselves to support [...]

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

By |2021-06-30T23:54:09+00:00June 10, 2019|Uncategorized|

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 [...]

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NYC Motor Vehicle Collisions Data in DB4IoT

By |2021-07-01T17:15:36+00:00April 10, 2019|DB4IoT News, DB4IoT with INRIX Trips, The Internet of Moving Things, Uncategorized|

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 [...]

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

By |2021-07-01T17:23:14+00:00December 19, 2018|DB4IoT News, DB4IoT with INRIX Trips, The Internet of Moving Things, Uncategorized|

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 [...]

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Deriving Greenhouse Gas Emissions Estimates from Connected Vehicle Data

By |2021-07-01T17:46:11+00:00October 31, 2018|DB4IoT News, DB4IoT with INRIX Trips, The Internet of Moving Things|

Eimar M. Boesjes, CEO, Moonshadow Mobile Joshua Skov, Industry Mentor, Lundquist College of Business, University of Oregon October 26, 2018 What does the carbon footprint from transportation look like? In particular, how could you map it? Typically, carbon footprinting exercises for local and regional jurisdictions deliver highly aggregated results. Even when the unit of analysis is geographic, the data is all about pie charts and tables. The results for New York City are...for all of New York City. Meaningful and important, but it leaves us missing something truly geographic [...]

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Making Better Transit Planning Decisions by Identifying ITS Data Errors

By |2021-07-01T20:30:42+00:00April 13, 2018|DB4IoT News, Route Analyst GTFS, The Internet of Moving Things, Uncategorized|

Over the last few decades public transit agencies have installed CAD/AVL systems on their buses for Computer Aided Dispatch and Automatic Vehicle Location. CAD/AVL systems capture data measurements of the location of the bus, number of passengers, delay, speed and many other variables, often as frequently as every five seconds. The result is a huge trove of data that can provide a wealth of information and insights about the operation of a transit agency. Data in these large quantities, however, always contains a significant number of errors. If charts, graphs [...]

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