Tag: Internet of Things

WeAre 4 Children: digital technologies for sport and youth wellbeing

Posted on | by Beatrice Grillo | Leave a Comment on WeAre 4 Children: digital technologies for sport and youth wellbeing

The Politecnico di Milano E⁴SPORT Laboratory has designed a T-shirt fitted with sensors – “smart garment” – to collect data on the wellbeing of children aged 11 to 12 during sport activities.

 

Physical activity during childhood is of the utmost importance because it builds muscle strength, develops bone structure, improves blood circulation, strengthens the immune system and teaches children how to share and socialise with their peers. However, the recent pandemic has led many children to give up doing physical activity to embrace more sedentary lifestyles.

Amateur sport clubs have always been important actors in helping children grow through sport, supporting them in the creation of a mind-body equilibrium.
Today, this task can also be carried out with the use of new tools: thanks to digital technologies, this objective can be achieved using methods that were inconceivable in the past. In particular, technologies related to the Internet of Things (IoT) – such as smart garments, smart watches, smart bracelets, movement and posture sensors, etc. – once only available to the most prestigious sport clubs, could also be adopted by amateur sport clubs to gather relevant data “from the field” related to the quality of training, sporting performance, and the physical and mental wellbeing of children.

In this context, the Politecnico di Milano Department of Management, Economics and Industrial Engineering and Department of Design, in collaboration with the U.S. Bosto Sport Centre in Varese, have developed an innovative project to understand how digital technologies can contribute to the wellbeing of young footballers, and improve their sporting performance.
The “WeAre 4 Children” research project has been approved by Politecnico di Milano Ethics Committee and will involve 20 young footballers from U.S. Bosto who, during their weekly training sessions in Capolago and friendly matches, will wear a sensor-fitted T-shirt capable of collecting data on their sporting performance and physical wellbeing. The monitoring will take place through biometric sensors installed in the T-shirts themselves, including accelerometers, heart-rate monitors and specific motion capture sensors that can detect real-time information on parameters such as cardiac activity, posture, breathing, energy consumption and mood.

Politecnico di Milano and U.S. Bosto have engaged with partners in the Varese area. In particular, TK Soluzioni (an ICT company from Saronno) will provide support in creating the platform that will be used to integrate the data collected, Alfredo Grassi (a textiles company from Lonate Pozzolo) will offer its expertise for the design and production of the T-shirt, and the Centro Polispecialistico Beccaria health centre’s Sports Medicine Unit in Varese will monitor the physical and postural data.

The project is conceived as a feasibility study, aimed at establishing whether the digital solution developed ad hoc is appreciated by young footballers, their families and their trainers, and whether the data collected are reliable and the system works correctly in different scenarios of usability (training, matches, etc.).

The Department of Management, Economics and Industrial Engineering research group, headed by Professor Emanuele Lettieri and Dr Andrea Di Francesco, Engineer, project manager and researcher at Politecnico di Milano “E4Sport” interdepartmental Laboratory, will assess the impact that the project could have on U.S. Bosto’s extended community, as well as its economic-financial sustainability, with contributions from all of the project’s partners.
The ambition is to be able to extend the tested solution to other amateur sport clubs, including other sports in addition to football.

 

 

For further information: https://www.e4sport.polimi.it/weare4children/

Machines? Smarter and smarter!

Posted on | by Veronica Rafaniello | Leave a Comment on Machines? Smarter and smarter!

Exploring artificial intelligence and machine learning, technologies that bring accelerating change to our habits (and those of businesses)
 

 

Algorithms that can anticipate people’s tastes. Tests that can provide early diagnosis of a series of illnesses or predict which mechanical components are most likely to fail. Applications in a broad array of other fields, from manufacturing, marketing, and social media to voice recognition and self-driving cars. If the future is already here, this is partially thanks to artificial intelligence and one of its components: machine learning.
“Machine learning is a discipline that develops algorithms to make machines intelligent, that is, able to learn from past experience and make decisions regarding the future,” explains Carlotta Orsenigo, Associate Professor of Computer Science at the Politecnico di Milano and expert in machine learning algorithms.
“The advantages are enormous, also economically: more revenues at lower costs. Better forecasting of demand allows us, for example, to optimize stock management and offer better service to our customers.”
Carlotta Orsenigo is also co-director of a master’s program in data science at the Politecnico di Milano School of Management, whose graduates may find work in the business sector. “The International Master’s Program in Business Analytics and Big Data is addressed to people who have a degree in science or economics and less than five years of work experience. The objective is to develop competencies in three different areas: technology, methodology, and business. The one-year program prepares students for a job market with a very high rate of placement.”

Predicting demand

The key figure in machine learning is the data scientist, who analyzes data and develops algorithms that make it possible to use similar data as an effective prediction (and decision-making) tool and also interfaces with key company representatives (head of marketing or production, for example) on specific objectives.
“Machine learning can be very useful in retail for analyzing and predicting demand for products and services. Based on what customers have bought in the past, predictions are made as to what they will buy in the future. Likewise, the algorithm can analyze an analogous customer pool, that is, one with characteristics similar to our own, to predict what our customers will choose” continues Orsenigo.
The other aspect of demand prediction are recommendations, i.e., the suggestions that big players such as Amazon or Netflix make to their customers (If you liked that film, you’ll also like this one! Are you looking for something to read? Readers with similar tastes also enjoyed this one!). The intelligent machine processes a huge quantity of data and extrapolates patterns and trends without any help from humans.

A host of applications

“Another field of application is the manufacturing sector. In this case, the data to be analyzed are collected by the various sensors. Here we are getting into the Internet of Things (IoT). This makes it possible to identify potentially defective pieces in advance and prevent future failures.”
Actually, the most important field of application of machine learning is medicine and medical science. “The analysis of genetic expression, for example, allows for the detection of patterns between healthy and unhealthy people and the design of targeted diagnostic tests” says Orsenigo.
Another very important area is voice recognition /vocal interfaces, as we have seen from the success of Alexa and similar virtual assistants. “Our generation still prefers the option of typing, but young people are increasingly used to interacting vocally with their devices.”
And there are also chatbots, applications designed to simulate human conversation and learn from their interlocutor (tone of voice, topics of conversation, questions asked…) so they can provide increasingly well-targeted answers.
Not to mention self-driving cars…
In a word, the future is still there to be written—sorry, coded.