1 INNOVATION DIVE

Urban Lab and Innovation&Analytics Lab merged forces to find and develop the most disruptive innovations around five challenges: Mobility, Waste Management, Parking, Pollution, and Emergency. The Innovation Deep Dive will be divided into three parts: (1) Student Challenge, (2) Research for Empathy, and (3) Open Innovation Co-Creation, all steps based on Design Thinking methodology.
The Research for Empathy will be conducted by labs researchers and design thinkers with the main goal of identifying unique insights for the development of disruptive innovations. In order to achieve our goal, netnography and in-depth interviews with extreme users will be performed.
The Student Open Challenge will be performed by NOVA IMS students, where the goal is to design a possible disruptive innovation. Each of the groups will be dedicated to one of the five challenges presented. As for the process to identify the disruptive innovation, the students will be guided by specific innovation prompts in the Inspiration and Ideation phase for future project development.
The Open Innovation Co-Creation session is based on a 3 days hands-on workshop. It will be exclusively for participants registered in this activity.

5 CHALLENGES

MOBILITY

MOBILITY

Evaluation and prediction of patterns and behaviours of micro mobility in the city of Lisbon.
To support new planning and management approaches altogether with new tools to evaluate impact and prediction of behaviours.
Learn More
WASTE MANAGEMENT

WASTE
MANAGEMENT

Identification of patterns/profiles and solid waste production prediction in the city of Lisbon.
To identify patterns to support the prediction of the production of urban waste associated with a variety of context information.

Learn More
PARKING

PARKING

Identification of patterns and prediction of parking in the city of Lisbon to improve surveillance efficiency.
To create new models either to predict or to generate viable alternatives for illegal parking in the city.

Learn More
POLLUTION

POLLUTION

Elaboration of predictive models for the propagation of liquid and atmospheric pollutants in the city of Lisbon.
To develop predictive models for the propagation of liquid and atmospheric pollutants.

Learn More
EMERGENCY

EMERGENCY

Identification of patterns and predictive modelling of traffic accidents.
To deploy a prediction model in PGIL, where it will provide the day before, the streets and periods of the day in which is expected the occurrence of traffic accidents.

Learn More

NEWS AND EVENTS

Image
Image
Image

OUTPUTS STATUS

Activity 1

Data preparation and open data infrastructure assessment

Done (2 of 2)

100%

Activity 2

Services analytics refinement and HPC preparation

Current (3 of 4)

75%

Upcoming (1 of 4)

25%

Activity 3

Co-Creation Labs: perform experiences and validation by cities

Current (1 of 4)

25%

Upcoming (3 of 4)

75%

Activity 4

Dissemination and communication of results

Done (1 of 5)

20%

Current (2 of 5)

40%

Upcoming (2 of 5)

40%

Activity 5

Future sustainability

Upcoming (1 of 1)

100%

Activity 6

Project management

Done (1 of 3)

34%

Current (1 of 3)

33%

Upcoming (1 of 3)

33%

5 PARTNERS

Image
Image
Image
Image
Image