CSPs empowering smart cities:
TM Forum award winning Connected Citizens Catalyst
The smart cities opportunity is complex and includes many stakeholders collaborating to deliver an interoperable and open smart city environment. The opportunity for CSPs in the development of Smart Cities cannot be underestimated, not only from the perspective of innovating and development of new services but also in helping cities and communities to be sustainable and efficient.
TM Forum’s Smart City Enabling Digital Platform, Connected Citizens Catalyst, is a proof-of-concept focused on bringing together cities, CSPs and technology companies to deliver smart services for a cleaner, safer and efficient city environment for citizens, businesses and visitors.
The objective of developing a platform that delivers the digital capability for smart services in today’s cities is to enable developers and service providers to create and deploy innovative services for cities and its citizens.
The catalyst focused on developing a smart city platform enabling cities to focus on the following areas:
This use case supports the smart city vision of becoming more sustainable and broad-based while fostering improved communications between the different stakeholders. In the context of a city aiming to create an eco-friendly and sustainable city environment, its citizens need to be incentivised to leave their cars outside the city and use “Green Mobility Services”. The city plans to reward the citizens for their green mobility journeys on eco-friendly modes of transport in Nice including Velo Bleu bikes, e-cars and city trams.
By using green mobility services, citizens receive gamification points and become more environmentally aware. Transport service providers profit from revenue increases resulting from increased usage, data sharing opportunities and building stronger brand awareness. The city benefits by way of reduced traffic congestion (with fewer cars entering the city), a cleaner environment and more engaged citizens.
The Connected Citizens Catalyst has developed a cloud-based platform, or data hub, for smart cities that uses TM Forum Open APIs and software-defined networking. It enables new business models supporting the TM Forum’s Smart City Manifesto and provides the digital capability for services that deliver cleaner, safer, more adaptive and efficient city environments for citizens, enterprises and visitors. The catalyst is aligned to the UN SDG1 principles that support making cities sustainable.
Blockchain-based loyalty and a rewards platform are included to ensure that the right set of contributors (citizens, service providers and city) are recognized and rewarded for their contribution in smart planning and development. The goal is that such loyalty programs can make the smart city vision more sustainable and broad-based, and foster improved communications between the different stakeholders.
The Connected Citizens platform provides a secure environment for developers and service providers to easily create and deploy innovative services for cities and its citizens.
CSPs are key stakeholders in moving along smart cities projects. This catalyst has given CSPs more insight into the priorities of citizens in the context of smart city services and how they can improve quality of life. These insights in turn are valuable for CSPs to map into their own solution propositions in domains of network connectivity and digital services propositions.
The catalyst combines technologies from participating partners, each providing components of the overall solution.
Following completion of phase 2, the catalyst team has taken the concept out of the lab and is aiming to implement future live projects with partner cities across France. Phase 3 of the Connected Citizens Catalyst will employ the theme, “Turning Vision into Reality”, and following release of an MVP model, a “live” platform will be created based on the PoC delivered in phase 2. The next phase of the catalyst will also incorporate Artificial Intelligence (AI) methods to aggregate, store and analyse data using Machine Learning (ML) techniques.