Periodic Reporting for period 2 - AI4Cities (AI accelerating Cities transition to carbon neutrality)
Reporting period: 2020-12-01 to 2022-12-31
The cities of Amsterdam, Copenhagen, Helsinki, Stavanger, Tallinn, and Île-de-France (Paris region) are like-minded cities committed to become carbon neutral by 2050 at the latest. Their goal has been translated into exhaustive carbon neutrality strategies and plans with action points. AI4Cities was created to support the Cities Climate neutrality goals which are helping to turn their plans into action under two domains, mobility and energy.
There was clear demand on using data-driven methods to improve resource-efficiency and, while the amount of data increases, big data and AI are seen as playing a significant role in the cities’ data platforms.
The following topics were considered during the project.
The Proof-of-Concept (PoC) and the validation of the AI applied to climate mitigation context, to encourage further sustainable procurement of AI based solutions by the cities participating to the project.
Analysis of defragmentation of the market and potential elaboration of standards for public procurement in the domains of Mobility and Energy.
Analysis of the usage of the PCP methodology as a means to:
1) Encourage procurement of AI solutions Mobility and Energy domains for the benefit of a sustainable future
2) Create new market opportunities for AI in the GHG emissions mitigation market
Videos:
AI4Cities 1 minute: https://youtu.be/sqPLfTAbp_A
AI4Cities by Cap Digital https://youtu.be/3Kv0hHcNV-s
There was clear demand on using data-driven methods to improve resource-efficiency and, while the amount of data increases, big data and AI are seen as playing a significant role in the cities’ data platforms.
The following topics were considered during the project.
The Proof-of-Concept (PoC) and the validation of the AI applied to climate mitigation context, to encourage further sustainable procurement of AI based solutions by the cities participating to the project.
Analysis of defragmentation of the market and potential elaboration of standards for public procurement in the domains of Mobility and Energy.
Analysis of the usage of the PCP methodology as a means to:
1) Encourage procurement of AI solutions Mobility and Energy domains for the benefit of a sustainable future
2) Create new market opportunities for AI in the GHG emissions mitigation market
Videos:
AI4Cities 1 minute: https://youtu.be/sqPLfTAbp_A
AI4Cities by Cap Digital https://youtu.be/3Kv0hHcNV-s
Phase 1 Call for Tenders started the period and we received 97 tenders where 41 solutions were selected to do the solution design in Phase 1, 21 teams in Lot 1 - Mobility and 20 teams in Lot 2 - Energy.
In Phase 2 the number of teams was halved to 20 (10+10) to prepare a working prototype.
For Phase 3 to pilot the solutions in the cities selected three the most potential solutions to Lot 1 and four solutions to Lot 2 which are following:
Lot 1 - Mobility
MarshallAI consortium (Ix3)
Vianova consortium (MPAT Tool)
Nommon consortium (Avenue)
Lot 2 - Energy
Building Energy Efficiency consortium (BEE)
Enerbrain Ltd. (Spike)
C.in-City consortium
Holoni consortium
All work related to the Lots and challenges have done parallel and together with the lot leaders and other project partners.
KPIs - Outcomes
O.1) A minimum of 6 novel prototype solutions with proven impact in reducing Cities GHG emission
● Open Market Consultation: 100 companies engaged in OMC activities -> Achieved - 8 online events (Covid), total number of attendees +900
● RfT / Phase 1 call: 40 Contractors selected -> Achieved - RfT: 97 tenders in total, - Phase 1: 41 contractors selected
● Phase 2 Call-off: 20 Contractors select -> Achieved - Phase 2: 20 contractors selected
● Phase 3 Call-ff: 6 Contractors selected -> Achieved - Phase 3: 7 contractors selected
O.2) Developed action group of cities procurers and related networks with particular focus on AI applied to Climate emissions
● Enlarge preferred partners group to: 15 City procurers and 4 international networks of Cities -> Achieved partially - 12 city procures
O.3) Empower SMEs to take risks in the development and trial of ambitious ICT based solutions to support Cities Carbon Neutrality plans and action points
● Successful implementation of 12 Phase 3 pilots (2 per city) -> Achieved - 13 implemented pilots (6 in two cities, one in one city)
● Targeted international media showcases for the 6 final Solutions -> Achieved - Phase 3 contractors participated in World Summit AI -fair in Amsterdam (Nov. 2022), - Final online solution demonstrations (29.9. Phase 2 suppliers included; 13.12. pitched of the piloted solutions)
In Phase 2 the number of teams was halved to 20 (10+10) to prepare a working prototype.
For Phase 3 to pilot the solutions in the cities selected three the most potential solutions to Lot 1 and four solutions to Lot 2 which are following:
Lot 1 - Mobility
MarshallAI consortium (Ix3)
Vianova consortium (MPAT Tool)
Nommon consortium (Avenue)
Lot 2 - Energy
Building Energy Efficiency consortium (BEE)
Enerbrain Ltd. (Spike)
C.in-City consortium
Holoni consortium
All work related to the Lots and challenges have done parallel and together with the lot leaders and other project partners.
KPIs - Outcomes
O.1) A minimum of 6 novel prototype solutions with proven impact in reducing Cities GHG emission
● Open Market Consultation: 100 companies engaged in OMC activities -> Achieved - 8 online events (Covid), total number of attendees +900
● RfT / Phase 1 call: 40 Contractors selected -> Achieved - RfT: 97 tenders in total, - Phase 1: 41 contractors selected
● Phase 2 Call-off: 20 Contractors select -> Achieved - Phase 2: 20 contractors selected
● Phase 3 Call-ff: 6 Contractors selected -> Achieved - Phase 3: 7 contractors selected
O.2) Developed action group of cities procurers and related networks with particular focus on AI applied to Climate emissions
● Enlarge preferred partners group to: 15 City procurers and 4 international networks of Cities -> Achieved partially - 12 city procures
O.3) Empower SMEs to take risks in the development and trial of ambitious ICT based solutions to support Cities Carbon Neutrality plans and action points
● Successful implementation of 12 Phase 3 pilots (2 per city) -> Achieved - 13 implemented pilots (6 in two cities, one in one city)
● Targeted international media showcases for the 6 final Solutions -> Achieved - Phase 3 contractors participated in World Summit AI -fair in Amsterdam (Nov. 2022), - Final online solution demonstrations (29.9. Phase 2 suppliers included; 13.12. pitched of the piloted solutions)
PCP focuses on radical innovation and is meant for services, tools or products that are not yet on or close to market.
In this PCP, competing companies and developers werewill be given the opportunity to come up with innovative ideas for new digital-based solutions, built on AI and related key enabling technologies including 5G, IoT, Cloud computing and big data applications, with the goal of helping Cities become carbon-neutral.
All the Buyers Group cities havehas set targets to become carbon neutral by 2050 at latest and the most ambitious is Copenhagen which wants to achieve it already by 2025. Average 82% of CO2 emissions in the western European cities comes from energy and transportation. The cities piloted multiple AI4Cities solutions within the different maturity levelslevel.
The piloted solutions were selected to offer to the cities the possibility to test novel solutions with potential to help Cities fulfil their carbon neutrality goals and test the uptake of AI based tools, but which due to their nature, are not easily to be there which presented ideas that are not easy to implement directly implementable into the cities infrastructure, due to multiple barriers, such as need for training, regulatory approval, incompatibility with existing IT tools and systems like BMs, complex coordination requirements between while there are many e.g. other stakeholders, including other vendors, different public and private users, etc. involved too or can bring added value for the existing systems like BMSs. AI4Cities provided valuable results, beyond the solutions developed, both in terms of how to run such type of challenge based innovation procurement processes, as well as, the need to provide support to multiple stakeholders, particularly, user groups, and connected IT system managers. The process taught to the cities how much time or work the integration can take and who should be involved in.
Advantages of AI
The AI was seen as an essential component of all the solutions that were piloted in Phase 3. Indeed, the solutions would not have worked or would have been very different and less efficient without AI.
AI is, of course, always reliant on available data. In the piloting Phase, all solutions were able to get sufficient data to work properly. However, when scaling the solutions outside of the Buyers group cities, availability of data can be a challenge. On the other hand, two of the suppliers (Enerbrain and MarshallAI) are able to mostly avoid that challenge by also gathering their own data. Evaluators deemed that quality of the AI was adequate or good in every solution and in some cases were used for innovative purposes.
CO2 emissions estimation
Part of the One of the main objectives of the AI4Cities challenge was project was to push the market to develop come up with solutions capable of helping cities tothat lower CO2 emissions. The buyers group hired UseLess Company to help verify and validate the suppliers’ CO2 reduction methodologies and calculations during Phase 3 of the project. The UseLess company determined that each suppliers’ emission reduction and calculation methodologies were credible. The table below shows the reported emission reduction potential of each supplier, based on their pilot.
Also, UseLess concluded that tThe emissions reduction figures of different suppliers are not comparable with each other, because the scope of each pilot was different and some of thepart of the solutions have an indirect method for reducing CO2 emissions, which made in not possible to measure themis why CO2 reductions couldn’t be measured during the pilot, also due to time constrains and local weather conditions during the pilot stage. Therefore, Instead the figures presented are estimations/simulations if the solution was in use for a whole year.
In this PCP, competing companies and developers werewill be given the opportunity to come up with innovative ideas for new digital-based solutions, built on AI and related key enabling technologies including 5G, IoT, Cloud computing and big data applications, with the goal of helping Cities become carbon-neutral.
All the Buyers Group cities havehas set targets to become carbon neutral by 2050 at latest and the most ambitious is Copenhagen which wants to achieve it already by 2025. Average 82% of CO2 emissions in the western European cities comes from energy and transportation. The cities piloted multiple AI4Cities solutions within the different maturity levelslevel.
The piloted solutions were selected to offer to the cities the possibility to test novel solutions with potential to help Cities fulfil their carbon neutrality goals and test the uptake of AI based tools, but which due to their nature, are not easily to be there which presented ideas that are not easy to implement directly implementable into the cities infrastructure, due to multiple barriers, such as need for training, regulatory approval, incompatibility with existing IT tools and systems like BMs, complex coordination requirements between while there are many e.g. other stakeholders, including other vendors, different public and private users, etc. involved too or can bring added value for the existing systems like BMSs. AI4Cities provided valuable results, beyond the solutions developed, both in terms of how to run such type of challenge based innovation procurement processes, as well as, the need to provide support to multiple stakeholders, particularly, user groups, and connected IT system managers. The process taught to the cities how much time or work the integration can take and who should be involved in.
Advantages of AI
The AI was seen as an essential component of all the solutions that were piloted in Phase 3. Indeed, the solutions would not have worked or would have been very different and less efficient without AI.
AI is, of course, always reliant on available data. In the piloting Phase, all solutions were able to get sufficient data to work properly. However, when scaling the solutions outside of the Buyers group cities, availability of data can be a challenge. On the other hand, two of the suppliers (Enerbrain and MarshallAI) are able to mostly avoid that challenge by also gathering their own data. Evaluators deemed that quality of the AI was adequate or good in every solution and in some cases were used for innovative purposes.
CO2 emissions estimation
Part of the One of the main objectives of the AI4Cities challenge was project was to push the market to develop come up with solutions capable of helping cities tothat lower CO2 emissions. The buyers group hired UseLess Company to help verify and validate the suppliers’ CO2 reduction methodologies and calculations during Phase 3 of the project. The UseLess company determined that each suppliers’ emission reduction and calculation methodologies were credible. The table below shows the reported emission reduction potential of each supplier, based on their pilot.
Also, UseLess concluded that tThe emissions reduction figures of different suppliers are not comparable with each other, because the scope of each pilot was different and some of thepart of the solutions have an indirect method for reducing CO2 emissions, which made in not possible to measure themis why CO2 reductions couldn’t be measured during the pilot, also due to time constrains and local weather conditions during the pilot stage. Therefore, Instead the figures presented are estimations/simulations if the solution was in use for a whole year.