“OCTO Insight Radar Observatory”
Data analysis has gradually become central for the development of businesses and the growth of markets: manufacturing industries, public companies, utilities and cities have to face the challenge of an almost rapid digital transformation that has disrupted traditional business models, processes and most definitively a the way of life across society.
During the last decades, the IoT (Internet of Things) and the pervasive intelligence distributed in a lot of daily used objects have determined the generation of a huge quantity of Data as well as a new capabilities to share information between people and machines: apps, sensors, socials platforms are part of this new communication model.
This revolution, also defined asthe Fourth Industrial Revolution, has allowed a data-driven strategic approach for managers and business owners. With applications growing in interest, both in real time tasks and in the decisions making activities, thanks to their capabilities of being scalable and adaptable, increasing the effectiveness of the daily operations.
Also the data acquisition process has become more and more complex involving different channels with a growing demand of integration, which is highlighting the important role of platform as enablers for applications able to distribute benefits to different cooperating stakeholders.
The impact of the Industry 4.0 has also revolutionised the mobility market: road infrastructures, connected and autonomous vehicles, new on board systems for safety, real-time information and active cooperation between centralized data centers and peripheral sensors like cameras, are influencing today’s transportation.
The Smart City Observatory’s latest report, done by Politecnico of Milan in collaboration with Doxa,on the Smart Mobility and Smart Cities markets growth, has confirmed the central role of data analytics. Its importance is escalated through several integrated projects enabled by the analysis of data collected, with the goal of improving the safety and life quality of the citizens.
From the perspective of the OCTO Insight Radar Observatory, the newborn era of “smart things” is setting a network of relations between distributed “objects-people” with a complexity never experienced in human life, full of opportunities but also with some points of concern. This high connected world requires the orchestration of the “value crossed links”, very different from the “value chains” we are used to. The governance of the networks needs to have a complete picture of the processes, context and stakeholders involved; how each node of the network contribute to create a virtuous circle between where data are generated, were they are analyzed and transformed into information, and where they go (links between the nodes) as new knowledge to improve an existing service. A digital twin of the real world is built on these nodes and connections allow a new strategic approach based on insights derived by the integration of different resources into business workflows and, much more relevant, able to demonstrate the effect of the actions based on facts and data driven analysis.
In this Smart Things Universe, mobility is a well representative example: i) connected vehicles generate mobility data, ii) mobility data is processed to derive information about behaviours and patterns, iii) patterns are used from the smart city operators and mobility managers to support users improve the quality of their journey. So the virtuous circle starts from a connected vehicle and user, returning as a new profiled service to the citizens.
Data as a Smart City accelerator
The Smart City Observatory of the Politecnico di Milano in collaboration with Doxa presented a research that shows -on an annual basis- a 23% growth of the Smart City market in Italy. The research underlines also the aim of the various players, to continue to invest in this sector by adopting innovative and connected solutions to improve the users’ lives and safety.
According to GlobalData, Europe’s smart city market value was the highest in 2022 and is projected to grow at a CAGR of 7.9% between 2022 to 2026. On a global level, CAGR is expected to be marginally higher at 8.1%, as APAC countries invest heavily in smart city initiatives to enhance the quality of life for their residents and address urban challenges. Global growth is also strongly driven by the Smart Transportation segment which is projected to witness the highest growth over the forecast period with a CAGR of 9.5%.1
Projects and tools on the advancement also include the use of ‘Digital Twins’, i.e. virtual models that replicate the functions of physical assets, through which data interpretation can be used for predictive maintenance, machinery modelling, product, process and resource optimisation. The Digital Twins virtual replication is only possible thanks to the data collected. These models tracks the life cycle of the physical assets and uses real-time data sent by sensors to simulate performance and monitor operations.
It is important to specify that “Digital Twin” models have existed for several years, but only in recent years has it been recognized and shown potential. In fact a recent McKinsey research study2 highlighted that Digital Twins can boost profits by up to 10%, reduce time to development, production and distribution time by more than 50 percent, and improve product quality by more than 25%. It is important to specify that the period examined by the research was the years 2020-2022. More recently, PwC published a paper on ‘How digital twins can make smart cities better’, believing that digital twin technology will have a vital role to play in managing the next phase of urban development in a safe, efficient, cost-effective and more sustainable way.3
The POLIMI research likewise highlighted how Digital Twins that originated in the private sector and nowadays are conquering the Public sector too – more and more big cities are equipping with them – and one of the areas of greatest interest for investors is public security. In recent years, in fact, the investment in this area has gradually increased. Today the majority of active projects to improve urban security are based on the collection and analysis of data for specific geographical area monitoring.
Thanks to the precise analysis of connected data between devices and tools, it is possible to both draw user behaviour and predict it, thus supporting new plans for cities, for public transportation and additional services to reduce the congestion on the roads. Therefore, connected and integrated data make it possible to create a tailored security model suitable for specific needs.
Furthermore, according to Capgemini, 60% of organisations across major sectors are leaning on digital twins as a catalyst to not only improve operational performance, but also to fulfil their sustainability agenda. By being able to simulate the physical world, digital twins can help organisations to better utilise resources, reduce carbon emissions, optimise supply and transportation networks, as well as increase employee safety. The report also reveals that digital twin implementations within major industries, are set to increase by 36% on average over the next five years.4
The research, therefore, underlined how the data collection and analysis it is fundamental, not only for the growth of the target market but also for related businesses.
Collaboration between public entities and private companies for “digital twins” data analysis is crucial for effective urban planning and decision-making. Private companies bring technical expertise, innovation, and scalability to the table, helping city governments overcome resource constraints. The collaboration enables seamless access to diverse datasets, integration of advanced analytics algorithms and sector-specific insights. It also addresses data privacy and security concerns while realizing cost savings from efficiency gains. By working together, city governments can experience new step-by-step applications, field testing their citizens’ acceptance based on the main priorities and use cases. Effectively, learning by doing the new digital journey for all the stakeholders and private companies so they can harness the power of digital twins to enhance urban environments, optimize infrastructure, and cross fertilize new areas of business that improve the overall quality of life.
Smart mobility growing data driver
As one of the most relevant pillars of the smart cities, smart mobility is also growing in the business interest: according to the POLIMI (Politecnico of Milan), Italy has recorded a 16% growth in the last year in the sector of the connected car and mobility market. This growth is significant because 2022 was an ‘unusual‘ year, where the deficiency of raw materials had an impact on market, in which growth could have been much greater.
A connected car is a vehicle equipped with a device that can be installed within the vehicle in aftermarket or can be native, factory installed. The device is a kind of hub that collects data from the vehicle and sends them to a platform where they are further processed to serve multiple use cases and multiple business owners.
It is important to digress a little into history in order to comprehend the role of the connected vehicle business inside the mobility market. In fact, the introduction of connected vehicles into the market was a game-changer that opened up the possibility of seeing mobility as a service. The connected car was born in Formula 1 thanks to the integration of the first on-board computer in BMW’s team cars. Usage-Based Insurance (UBI) services disrupted the insurance market that is now proliferating with start-ups and innovation along the entire policyholders journey and traditional insurance processes like claims management, actuarial science and customer selection. Only recently, the connected vehicles model has been included in the urban mobility framework.
The capability of connected vehicles to communicate in a bi-directional manner with other systems outside the vehicle, by sharing data with other devices has been revolutionary for the improvement of road safety. Connected vehicles can detect hazards and provide timely warnings to drivers, helping them make informed decisions. The bi-directional communication enables vehicles to share information, facilitating collision avoidance systems that can automatically initiate safety mechanisms. Data analysis further aid in uncovering patterns in the collected data sets thereby assisting the driver in the following scenarios, including but not limited to:
- improving personal productivity using features such as traffic alerts,
- enhancing risk exposure by monitoring driving trends and providing personalized coaching feedback for risky driver behaviour.
- enabling prompt emergency assistance in case of accidents and other perilous scenarios.
Overall, these capabilities contribute to creating safer road environments and reducing accidents on the road.
The annual growth of this sector shows how connected cars are becoming – for public and private actors – necessary. Thanks to connected vehicle technology, in fact, it is possible to improve the productivity of fleets, to detect risky driving behaviour and reduce it, to guarantee timely and punctual maintenance of vehicles, but above all to generate precise data on fuel consumption and inefficient activities (e.g. leaving the vehicle idling when stationary) in order to take action to reducing them.
The growth of the “connected vehicle and mobility” sector stems from improvements in technologies associated with IoT and sensors, advancement in telecommunications networks, and general diffusion of public awareness in using telematics as a scalpel to control cost, risk and improve the services to the drivers. This has resulted in targeted data collection and analysis for segment specific use cases. By analyzing data from connected vehicles and various other sources it can assist in optimizing route planning, improve vehicle productivity, and construct optimal risk management programs for their fleets. Data analysis also enhances safety and security by detecting incidents and risks in real-time. It enables personalized travel experiences through understanding user preferences and behavior. Additionally, data analysis supports demand-responsive transportation systems and facilitates continuous performance monitoring and evaluation. Ultimately, data analysis drives efficient, sustainable, and user-centric transportation systems innovating the framework of the modern cities with a more data driven approach.
In the first part of Industry 4.0, the focus was on what data and how much data to collect, today the challenge has evolved and the focus is on “what really matters”: to find the right insights, to analyse them on a large scale in order to learn and make intelligent workflows capable to respond reactively and proactively to fast-changing conditions.
This trend is progressing with several projects already running, but still requires more resources to combine technologies such as 5G, edge computing, data analysis as part of the road infrastructure, cooperation with connected users and intuitive dashboards to support the decision making processes.
The experience of the past has taught us that collecting data without analysing means filling dashboards without proposing actionable steps. Fixing this involves setting up a holistic plan with a goal in mind, collecting the right data which serves the need and finally analysing this data with right polices and assumptions to ensure game-changing decisions for businesses and uncovering growth opportunities for the target segments. Organizations should prioritize a data analysis mindset, foster a data-driven culture, and implement robust data governance measures to ensure accurate, secure, and meaningful utilization of collected data.
Authors: Mirella Astarita, Andrew Lee, Tina Martino, Sujit Raghavan