[ui!] UrbanPulse - COCKPIT - Bad Hersfeld, Germany

The project established a “Smart City Lab” with the objective to improve traffic flow using the [ui!] UrbanPulse open data platform. There are two major drivers for this project:

    • Bad Hersfeld is a city in the centre of Germany with around 30,000 citizens that is known for its festivals, particularly the annual Bad Hersfelder Festspiele.
    • Due to its location the City is a preferred hub for major logistic firms. There are several major truck and car routes crossing the city putting 30,000 cars and trucks on roads in the city perimeter per day. All of Germany can be served within a 4 hour period from this location. While these companies create jobs, the associated traffic causes major issues around noise and pollution.

The city has a total of 5,000 parking spaces. On average, drivers spend 10 minutes per parking space looking for a free slot whilst covering a distance of 5 kilometres per search. Each parking space averages 2.5 searches per day. This equates to 56,000 kilometres or 1.4 times around the world per day to find a parking space. The situation becomes particularly challenging in the centre of the city where there are 250 parking spaces that attract 10 searches per day which increases on two days of the week when a farmers’ market is held.

The problems for city associated with the traffic flow and parking situation include:

    • Searching or parking in the main city centre causes unnecessary emissions
    • No or unreliable data from previous in-ground sensors
    • Driver frustration
    • Fear that local retailers in the city centre will lose clients to shopping malls, if efficient parking guidance is not available
    • Local residents very annoyed by noise and pollution levels
    • EU Government regulations requiring reduction of CO2 emissions

The city wanted to utilise smart city technology to improve traffic management and traffic flow management by providing parking information to citizens, tourists and logistics companies prior to entering the city.

[ui!] worked with the city to establish and trial a “Smart City Lab” with the goal of improving traffic management and traffic flow management, using the [ui!] UrbanPulse Management Platform. The project included:

    • Overhead sensor system monitoring all spaces to detect if a space is free or occupied. This data was sent to the UrbanPulse and combined with traffic information to send to traffic guidance LED signs at the entrance of parking areas and all in-bound streets and main streets entering the city
    • The availability of real-time data provides drivers with immediate wayfinding to free spaces to free spaces in all garages and on-street parking
    • Expansion of sensor system to park & ride locations
    • The city supported the development of a noise app, allowing citizens to identify noise hot spots.


Screen shot of City [ui!] COCKPIT of Bad Hersfeld (badhersfeld.urbanpulse.de)

The outcomes of the project include:

    • Drivers are able to make immediate, intelligent decisions
    • Reduced traffic emissions and saved time
    • The identification, resolution and monitoring of noise trouble spots
    • In bound drivers parking guidance gives a high chance indication that parking is available in certain car parks
    • Trade for local retailers has improved

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[ui!] UrbanPulse - traffic light assist - Germany

Council’s objectives were to improve traffic flow and reduce brake/acceleration patterns, contributing to reduction of its carbon emissions (target:20% by 2020) to meet EU 'Horizon 2020' goals. In December 2015, the Council Department of Transportation and [ui!] began a joint project to create the city’s first traffic app and open data platform for traffic data. The project has three components:

  • Traffic signal phase prediction
  • Information sharing
  • An open data portal

For all of these components the collection and dissemination of traffic data is at the core of our approach, as shown in the diagram below:

urbanpulse traffic 


[ui!]’s UrbanPulse open data platform has been used as the basis for a Traffic Light Assist system. In this project, [ui!] UrbanPulse integrates with the city’s traffic control system to predict short-term traffic light phase changes, and shares this information with vehicles. The solution allows the adaptive cruise control in the vehicle to adapt the car's driving pattern to minimise fuel usage and stopping time at lights.


[ui!] delivers traffic data to citizens, business and the automotive industry and is the foundation for new digital services for transport disruption and creates unique conditions for eco-driving through driver assistance systems.

The free traffic-app for citizens provides:

  • Qualitative visualization of traffic conditions
  • High degree of updating, which is particularly crucial in the inner city area
  • Construction Site information (both current and planned)
  • Optimized for smartphones

The information is also shared with Continental AG who then provides it directly to vehicles.



Some of the data collected by [ui!] UrbanPulse is also made available as open data. This data then be used as a basis for citizen services, and support the private sector and researchers in development of innovative transport applications

The real-time open data portal provides:

  • Aggregated detector readings
  • Historical data
  • Signal location plans and translation tables
  • Simple data format
  • Open for everyone

The decision of what data to release through the open data portal, and when, is made by the Council.

The open data portal is designed to be scalable so the city can expand its services by including any other urban data from real-time sensor data to real- time and historical data from any enterprise management system and data from 3rd parties such as weather forecasting sites.



Technical outcomes of the project include:

  • A new parameterized forecasting method for traffic signal phase changes with very low latency
  • Creation of a proven algorithm for traffic light prediction
  • Demonstration on Test Track with Web Application
  • A very low latency (0.6s. 1.1s) achieved by leveraging Microsoft Azure cloud technology and fast

communication channels

  • Scale-up to cover the entire city area
  • Communication to end devices over SSL / TLS
  • Client-side processing
  • Data anonymized and not re-identifiable

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[ui!] UrbanPulse - New Zealand

[ui!] was invited to work with Council to identify and scope a smart cities technologies pilot project within the smart city strategic direction of the Authority. The aims of the trial were to:

□ Create a ‘living lab’ for Council’s smart city vision and journey;
□ Provide a testbed for third party innovation, partnering and sharing;
□ Inform discussions around operational effectiveness, asset management and business processes;
□ Be a case study in Council’s evolution towards agile, fail-fast development and innovation; and
□ Allow Council to continue to experiment with data models including open data and 3rd party data sharing.

The preferred location for the trial was chosen because:

□ It has several important variables:

o Short and long term vehicle parking;
o Ferry terminal;
o Bus interchange;
o Pedestrian and cycling infrastructure for access to and from the ferry terminal; and
o A varying patronage throughout the day, including commuters, visitors, retirees, etc.

□ The parking area can be used to experiment with the parking sensor technology, and parking in both the short and long term lots will turn over frequently enough to produce interesting data.

□ Sensors (including parking sensors, IR cameras for people and/or traffic counting, CCTV cameras for security/people counting/traffic counting) environmental sensors, WiFi base stations) can be mounted on existing infrastructure, on new infrastructure (deploy smart poles with integrated technology), or on a mixture of the two. Which gives Council the opportunity to learn about the benefits/difficulties associated with each approach.

□ Smart poles were chosen as they can also be used for an Electric Vehicle charging trial.

□ There is significant interest in people-counting in the project area, in part to understand how people transition between the various transport modalities outlined above, and in part to gather insights that will shape the future commercial development of the ferry terminal.

□ The location affords interesting opportunities to integrate across, and apply analytics to, the diversity of data sources implied above (parking data, people- counting/tracking data from cameras and or WiFi-based counting , bus passenger data through Council’s transport cards, ferry passenger data through Council’s transport cards and environmental sensors).

NewZealandGoogleEarth screenshot of the trial location

The various sensors and public transport data have been connected to [ui!]’s UrbanPulse open data platform, which can be used for data integration, analytics and visualisation, as well as feeding data to existing Council projects. The existing free WiFi network in the city, which supports tracking, will also be integrated.

[ui!] delivered its UrbanPulse open data platform to meet Council’s business requirements. [ui!] sourced and managed the installation of multi-functional smart poles (including electric vehicle charging facilities), WiFi, environmental sensors, emergency calling, smart parking technologies (both above and in- ground solutions). The [ui!] UrbanPulse platform ingests data for these sensors and devices along with data from Council’s transport cards and transport information systems to provide Council with an integrated real- time view of:

□ People movement in the area (especially through the terminal building);
□ WiFi use;
□ Pollution levels;
□ Noise levels;
□ Public transport timetables;
□ Short and long term parking bay usage;
□ Commuter numbers (bus and ferry); and
□ Electric vehicle charger usage.

In conjunction with Council, [ui!] also developed a support process and a system for any customer queries associated with the Electric Vehicle charging facilities.

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[ui!] UrbanPulse - Queensland, Australia

In 2016 a major Council in Queensland (population approximately 350,000) adopted their Smart City Implementation Program to guide the deployment of Smart City solutions in a staged manner across the region. By using ICT to connect people, processes, data and things the Council is seeking to improve quality of life, stimulate economic growth and ensure environmental sustainability through their region.

[ui!] began working with the Council on its staged approach to smart city solutions with a year-long Smart City Pilot Project that trialled a number of smart city technologies in two cities. The objective of the project was to create a smart parking demonstrator; develop a better understanding of how citizens and visitors are using and moving around the coast; and, showcase smart city technologies to the public in the Smart Centre and Living Lab through the visualisation functionality of [ui!’s open data platform, UrbanPulse.

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Screenshot of the Council UrbanPulse Dashboard

Following the success of the initial pilot project [ui!] was chosen to develop the Smart City Regional Management Platform for the Council project. This project is part of the Council’s broader strategy to develop an integrated Smart City that will generate high value New Intelligent Systems (formally Business Intelligence) and provide access to internal and external clients. It includes a major City Centre at the green-field site in the middle of the city; continued development of the City’s smart technology precinct and activities in the wider Council’s coastal region to deliver benefits of smart city technology at scale.

[ui!] integrated 3rd party smart parking technology, WiFi, smart waste bin sensors, and data from public sources into [ui!]’s UrbanPulse open data platform to create a smart precinct demonstrator. [ui!] also

provided input into planning the green-field CBD site by identifying ways that data can be used to deliver new services to residents and/or improve city operations. As well as extending the number and reach of existing types of sensor data, [ui!] is currently working with Council to ingest data from new devices such as water quality sensors, built environment systems, public transport systems, different types of waste management systems and waste water systems. This work will provide Council with a platform management tool based upon real-time (and/or historical) data from a variety of infrastructure sources presented in an usable, visual format that allows them to view, analyse, forecast and combine information in a way that supports decision making and planning.

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