SmartRoad (Winter Road Maintenance)

This use case is dedicated to winter road maintenance in the Kolarctic region. It will be led by the Arctic University of Norway (UiT). We seek to investigate technology and organizational issues related to the utilization of public infrastructure for data collection and analysis, in particular, instrumentation of waste collecting vehicles.

This is particularly interesting for the regions on the west coast of the Kolarctic region. Sudden changes in the weather, between freezing temperatures and mild weather with rain, are common during the wintertime. This, in combination with the topography consisting of steep hills and fjords, makes the driving conditions challenging.

By measuring parameters and geometry related to the roads, which these vehicles are driving on, waste-collecting services can provide information of great value for winter maintenance of public roads, and for scheduling of own and other (commuter) services.

Measuring of road friction is considered to be one of the most relevant parameters to the arctic communities and should be implemented first. We plan to use one or two vehicles for the first season, and subsequently up-scale applications of our solutions to a fleet of vehicles in the next season. The project will contribute to preparing local infrastructure for disruptive information technology and providing value-adding services to the community.

The use case will include server-side analysis and cloud services for collection and visualization of collected data utilizing methods from artificial intelligence (AI) research is considered to be a part of this work package. Dissemination of results will be done by direct communication with the involved industrial partners, workshops and scientific publications. As some of the collected data may have a public interest, popularisation of the topics involved and news related publications will be considered.

This use case should include experimental set-up consisting of both low-end/consumer-grade electronics equipment and solutions which are more technologically advanced. The considered methods should have an element of trial-and-error to facilitate the discovery of new ways of utilizing emerging technologies, such as, for example, IoT.

Furthermore, a combination of 360 video and geometry measurement (by for instance, LIDAR), should be developed for this data collecting platform.

Hackathon task description

Applying salt in various forms for thawing ice, in combination with sand, is an efficient method to increase the road surface friction. The spreading of salt on the road surface has increased throughout the past two decades. The lower threshold for the needed amount of salt to ensure the efficiency of the method depends on the freezing temperature of the resulting salt/water mixture on the road. On the other hand, using too much salt is not optimal from an economic point of view and has negative impact on the environment.

Given a set of parameters measured along a road segment.

· Water thickness (mm)

· Surface temperature (degrees Celsius)

· Air temperature (degrees Celsius)

together with a meteogram forecasting, most notably,

· Temperature (degrees Celsius)

· Precipitation (mm)

Main objective:

To calculate the suggested amount of salt based on the measured parameters and meteogram.

· Establish a model

· Implement a prototype

The expected outcome is a graph plot showing salt amount vs. temperature.

Познавательные статьи:



Алгоритмические операторы Matlab

Конструирование и порядок расчёта дорожной одежды

Исследования учёных: почему помогают молитвы?

Почему терпят неудачу многие предприниматели?