Mobile World Congress is coming once again this year to Barcelona, from the 25 to 28th of February. Along with it comes its load of futuristic news and predictions concerning the mobile technologies. However, this year’s edition is expanding its reach beyond ‘just’ mobile by focusing on 5G as expected, but also including as main protagonists the Internet of Things (IoT), Big Data and Artificial Intelligence (AI). This natural evolution resulted in a rebranding of the event (MWC) to better reflect this widen scope.
For Urbiotica this new focus is good news considering that the development of IoT solutions for “Smart Cities” is the base of the company’s strategy, which implies challenges strongly related to these technologies:
Connectivity: to connect reliably wireless and autonomous sensors to our sophisticated platform, with the emergence of the NB-IoT protocol to simplify deployments and address new use cases.
Big Data: the platform concentrates most of the intelligence of the systems. It’s where billions of raw measurements sent by the sensors are processed to generate the useful information used by our customers and the people living and working in these cities.
Artificial Intelligence: although it’s more a challenge to come than a real insight in the actual structure of the solutions, Urbioticas’ vision and experience based on customers’ feedback is leading right there. Beyond the pure sectorial predictions expected through any IoT solution based on historical data and to help decision-making and planning, how can we let A.I. mechanisms define and execute daily tasks impacting on people mobility and well-being? Where do manager knowledge and user behavior stand in the amount of data collected, processed, and crossed with external sources of information? If in an industrial and controlled environment huge progress has been made in that way, in the Smart City sector, where external inputs of the system are so various as unpredictable, this step forward seems still quite far away.
Most of our customers, especially in the public sector, are still learning to use the new insight represented by a reliable source of continuous information provided by the IoT system. On one hand, they are making the most of the real-time benefit offered by guidance and alerting messages, and on the other, they are beginning to integrate to their mid and long-term strategic planning information brought by the analytics offered by the platform.
This is where we stand right now, not really due to a lack of technologies, but because of a progressive approach where each step is important in the learning curve. Next one will be conditioned by the will of the cities’ managers to improve their interaction capacity with the system, to influence on people behavior according to the situation and rules they have configured. Once this is fully controlled on a project basis and the patterns are perfectly understood, then will be the time for artificial intelligence.
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