Ignite Winners

Find out more about the Finalists and their Smart M.Apps.

1st Place: Tomasz Berezowski - Mind M.App

Tomasz Berezowski
The Wroclaw Institute of Spatial Information and Artificial Intelligence

Mind M.App


Tomasz and his team Marek Strzelecki, Iwona Kaczmarek, and Bartosz Majster created Mind M.App: The first application combining a graph data model with the professional geospatial platform. Mind M.App allows creating maps of associations between entities. Using it you can record complex knowledge gathered during research or investigation and combine it with external data sources using RDF technology. Once you have your mind map created you can discover hidden links, spatial patterns and infer new knowledge. In result you will be able to solve e.g. criminal case more quickly and in a more reliable way.

Read an interview with Tomasz.

2nd Place - Paul Geurts - Smart Emissions M.App

Paul Geurts

Smart Emission M.App


Smart Emission M.App visualizes air quality sensor data combined with regional data to allow both citizens and government to jointly discuss urban planning issues such as air pollution and sound pollution.

Read an interview with Paul.
Watch teammate Bas de Greef talk about the project.

3rd Place - Noel Khan - AiGIS: US Tax Maps

Noel Khan

AiGIS: US Tax Maps

United States

AiGIS: US Tax Maps Automatically georeferences US Assessor maps to GIS parcels. Rather than relating US Assessor maps and GIS data using attributes, leverage the spatial relationships between those datasets by quickly and automatically georeferencing US Assessor maps.

Watch Noel talk about his project. 

Andrew Kerr - Everybody Counts My Safari

Andrew Kerr

Everybody Counts


Everybody Counts: My Safari is an end-to-end turnkey product to harness the power of crowd-sourcing data. It uses public mobile app for data collection which includes a secure database and private, powerful, real-time data analysis tool.


Read an interview with Andrew.
Watch Andrew talk about his project.

Jens Hiestermann - GeoFarmer

Jens Hiestermann

GeoFarmer — A Monthly Crop Monitoring Tool

South Africa

GeoFarmer — A Monthly Crop Monitoring Tool analyzes growth stages of agriculture in near real-time. This app uses climatic data and satellite imagery to determine field-specific crop status. This app can be used by agricultural estimators, insurers, and commodity traders.

Watch Jens talk about the project. 

Jose Luis Barajas

Jose Luis Barajas



Agromapps organizes agricultural projects and provides information to agricultural professionals on stating goals, planning, incidentals, costs, incomes, and geospatial information.

Oscar Diaz

Gabriel Díaz
Oscar Díaz

Field Research Planner


Field Research Planner Efficiently create your marketing field research plan. Use the census data, select the survey area and relevant statistical indicators to calculate representative sample size distributed per administrative units within the area. Print the outcome as a PDF or download reports to hand out to your field team.

Watch an interview with Oscar.

David Dorrell

David Dorrell
Andre Olifer
Robert Lutz

aNoise Estimator

United States

aNoise Estimator estimates noise level at provided locations to enable informed decision making. Currently estimates traffic noise level based on traffic volume, distance from roads, and surface absorption.

Ute Gangkofner

Ute Gangkofner

Global Green Analyzer


Global Green Analyzer Compare vegetation time series data up to 16 years ago to discover trends and anomalies to make informed decisions on managing resources. Updated every 16 days, maps and diagrams present information about deficits, changes, and continuity of vegetation development and habitat potential.

Read an interview with Ute.

Irene Gobran

Irene Gobran

Heat Loss Probe


Heat Loss Probe Identifying Buildings with Poor Thermal Insulation. Classifies thermal aerial imagery and maps the heat loss. Encompasses the production chain: manipulates the images’ statistics, classifies and maps the result.

Read an interview with Irene.

Lukasz Lechowski

Łukasz Lechowski



.GEO Teach geography using localized games. Discover Your "neighborhood" and learn about spatial processes, environmental issues happening in your region or location playing this educational game. Get points and share your scoring with your friends. Teachers can use this teaching and learning app in the classroom to teach geography and environmental awareness. Students and parents can learn about their home state and county.

Read an interview with Łukasz.

Li Lin

Li Lin
Dr. Liping Di

Safe Neighborhoods

United States

Safe Neighborhoods Find safe neighborhoods by understanding the relationship between crime statistics, demographics, political boundaries, and other factors. General public can make decisions on safe travel destinations and relocation. Local agencies can understand the relationship between crime and census data to plan safety strategies.

Read an interview with Li.

Neil Meadows

Neil Meadows

Pixel Farm – Crop Analyzer


Pixel Farm — Crop Analyzer Monitor crop performance easily using GIS and remote-sensing data. Monitor crop performance quickly and accurately from a user-friendly dashboard with data from remote-sensing platforms (satellite, aerial, or UAV).

Read an interview with Neil.

Taiga Moroboshi

Taiga Moroboshi



SmartPort shows worldwide statistics of vessels around ports and informs us about the economic scales associated with them. Smart Port is mainly for International organizations or corporations striving to understand and update their global business strategy.

Read an interview with Taiga.

Chris Nankervis

Christopher Nankervis

Climate–Smart Crop

United Kingdom

Climate–Smart Crop delivers weather insights at the farm-field level. Compare side-by-side seasonal forecasts, historical observations, and climatologies to help you plan your crop protection and management strategies.

Read an interview with Christopher.

Laura Rutgers

Mieki Peeters-van Berkel

Dynamic Monitor for Predicting Charging Points Electric Transport


Dynamic Monitor for Predicting Charging Points Electric Transport provides information about strategic placement of charging points for policy and decision makers. A tool that:

  • predicts the most likely (public space) locations within a city for charging point requests;
  • provides an overview of the most suitable locations in public spaces for charging points based on spatial planning, user and network criteria;
  • Visualizes the usage of installed charging poles in public space.

Watch team member Cesar Blaauwgeers talk about the project. 

Stefano Picchio

Stefano Picchio

Smart AgriLand


Smart AgriLand Monitor crops saving money. Provides a user-friendly environment for monitoring your own crops over time. With Earth Observation images, you can manage your farm more precisely, saving money, time, and the environment. Select your crop from the map and monitor it using images from the sky!

See more about the project. 

Jinfei Wang

Jinfei Wang

Time Series Visualizer


Time Series Visualizer This Smart M.App lets you see space-time series imagery in a user-selected area. You can draw a polygon or sets of polygons and see spatial temporal statistics using graphs and tables.

Robert Widz

Robert Widz



POWER.PLANT Diagnoses the state of a crop by collecting data using satellite images, sensor data, or other sources and generates reports that make specific recommendations for further soil or plant treatment of your crop.

Shaun WIlliams

Shaun Williams

The SNAP M.App

United States

The SNAP M.App This M.App displays visual connections between points of interest on maps based upon a group attribute field. Connection links highlight associations based upon individuals or incidents which spotlights patterns and relationships beyond point reference maps.

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Watch IGNITE Interviews

Our IGNITE Finalists talk about the projects and why they are excited about Hexagon Smart M.Apps

IGNITE Contest Page

Visit the IGNITE contest page to see more about the contest and how the contestants got here!

Hexagon Smart M.App

Hexagon Smart M.Apps® provide a powerful, yet simple way to incorporate dynamic analysis into intelligent maps which not only model the world as it is, but as it will be.

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