4. Smart Cities platforms
I addressed industry platforms in the last posts noting the multitude of data that are created by industry processes and in perspective by the products as they will be used. I also pointed out the crucial role played by Digital Twins in that context (as Digital Transformation takes over and permeates industry).
Now, scale all that by at least two orders of magnitude and enter the smart city arena. Here the complexity is way higher. In an industry, and even in the manufacturing value chain involving several players, data are structured and the overall processes are well defined. Not so in a city.
A city is a living organism in a dynamical equilibrium, challenged every day by new situations. Besides, a fundamental component of cities is … citizens and they (we) are by nature unstructured.
A city generates an amazing quantity of data streams, mostly of them created independently from one another (Amsterdam was found to have 12,000 data sets -and corresponding streams, basically unrelated), and yet the real value is derived by applying correlation, data analytics, to these originally independent data streams. It is this variety and ever changing dynamics that make cities different from industry. Hence the need for specific support.
There are a number of platforms available whose main goal is on one side to bring in data from the variety of IoT (sensors) disseminated in the city, storing them in a way that data analytics can be effective and opening them up, in a controlled way, to third party use.
A crucial aspect in this data management is to ensure on the one hand privacy and on the other hand openness, so that those data can become valuable. This seems to be a contradiction in terms, yet it is exactly the goal of a city platform. Actually, the better a platform is at preserving data privacy and opening up data, the more valuable the platform.
Neutralisation of data is a first step but once you open up many data streams, correlation may circumvent neutralisation. More sophisticated approaches to privacy preservation have to be put in place. An approach is to create meta-data in the platform and release only these meta-data, not allowing the direct access to the raw data provided by sensors. In this way there is a hard decoupling that is more robust in preserving privacy. Another, complementary approach, is through some sort of watermarking/blockchaining the data values released by the platform so that it is possible to track their use and take action in case of improper usage.
Platforms operating in an industrial framework are tasked with ensuring the quality of the data, which implies making sure that the sensors providing the data are working in a proper way and within pre-defined tolerance range. On the contrary, platforms operating in a smart city framework are tasked with ensuring the quality of the meta-data, in spite of the possible low quality of the raw data provided by sensors. This is because the sensors are (usually) not owned by that entity (municipality) managing the platform. This is usually possible given the large number of sensors providing redundant data. This redundancy can be used to generate an accurate meta-data.
Another crucial difference between an industrial platform and a smart city platform is the support to reusability of services. Applications operating on an industrial platform are generally customised to the specific industrial environment they support. A different industry will develop its own specific application. A smart city platform should manage data and open data in such a way that applications developed for a certain city can be “re-farmed” with minimal effort for other cities.
This is what characterises, as an example, FIWARE. For full details on this platform, resulting from cooperative work promoted by the European Future Internet Program, look at their website. What I feel important here is to note that FIWARE is a platform designed to foster the Digital Transformation of cities, leveraging on technology but having as real goal the execution of the Digital Transformation, which implies supporting the variety of processes in a city in an economically affordable way. Part of this affordability is rooted in the possibility to re-use applications and services.