AI is late many small advances such as optimize fruit ripening, an artificial sense of smell, a system that improves student performance, learn more about Don Quixote or create a doll to accompany our elders.
These are curious and lesser-known examples of how artificial intelligence can be applied to our advantage on a smaller scale. Fifteen examples are worth mentioning.
Agricultural ripening
The Tekniker technological center, located in the Basque Country, has developed a tool for detect the characteristics or defects of bananas and optimize their ripening thanks to image processing based on artificial intelligence.
Neural network-based image processing is an artificial intelligence technique that can help develop solutions for sectors such as the food industry identify production and processing errors and improve product quality.
Using a deep learning model, it detects features or defects in images (more than 2,000) through artificial intelligence-based image processing.
The results of the work have made it possible to optimize the banana ripening process in order to offer the best quality product at any time of the year.
artificial smell
Researchers at Institute of Bioengineering of Catalonia (IBEC), in collaboration with the University of Cordobahave developed a technique, similar to an artificial nose, capable of analyzing the substances present in the aroma of a food at the molecular level and thus controlling its quality and traceability.
This artificial smell‘, which uses artificial intelligence to analyze the data, was able, for example, to differentiate samples of Iberian ham that had been acorn-fed from those that had been fed ordinary food.
School performance
Researchers at Universitat Oberta de Catalunya (Open University of CataloniaUOC) used artificial intelligence to design a system that improves student performance and reduces school dropout rates by detecting a subject’s risk of failure.
The University implemented this system with a pilot test with more than 552 first-year students of UOC’s economics and business degrees.
The system, which has been applied to two of the subjects taken by students, is called the Learning Intelligent System (LIS) and includes an early warning tool to alert teachers and students to the risk of subject failure.
It’s a system that works by processing all the information collected in the “data mart”, a institutional data center developed six years ago at the UOC that collects historical and current data on the academic life of students at the university.
Against woodworms and termites
The Sispatint project of the Instituto Tecnológico Metalmecánico, Mueble, Madera, Embalaje y Afines (Aidimme) is intended to monitor works of art such as altarpieces, canvases or altars, wooden structures in historic buildings such as markets or churches, although it can also be used in new constructions .
A sensor system to prevent the presence of woodworms and termites in works of art, which works thanks to artificial intelligence, and which has even attracted the interest of the Massachusetts Institute of Technology (MIT), will save millions in the preservation of historical heritage.
Water pollution
The Catalan company Fregata Space has created a program that combines big data and machine learning techniques to detect water pollution using satellite data, including the number of toxic agents present in ports, reservoirs, beaches, inland lakes and river mouths.
The software developed by the company provides information on the degree of contamination at different points on Earth by decoding, with algorithms based on artificial intelligence, satellite images of 20 constellations, i.e. more than 100 nano-satellites, which provide information on the level of contamination of the water to be analyzed.
Reconstruction of Pompeii
Artificial intelligence and robotics will help for the first time in the archaeological area of Pompeii, the city destroyed by the eruption of Vesuvius in 79 AD, to reconstruct remains and frescoes that are largely fragmented and difficult to reconstruct.
Thanks to“Repair“, an acronym for reconstruction of the past, thousands of fragments, like small pieces of a puzzle, will be rearranged using mechanical arms capable of scanning the remains, recognizing them using a 3D scanning system and place in the correct position
A doll to break the isolation
A Japanese toy company created a doll with artificial intelligence to converse, stay active and alleviate the feeling of isolation of elderly people following the outbreak of the COVID-19 pandemic.
Appointed Ami-chanthe doll was developed by Takara Tomy and has a facial or color recognition chip and an artificial intelligence that helps it develop a personality and vary its reactions and conversations depending on the frequency of attention and contact with it.
Ami-chan’s nerve center, measuring 30 centimeters in height for easy attachment, is located in the clasp on his chest, where the chip and AI were installed.
The doll, whose appearance is designed to simulate that of a young granddaughter and whose voice is that of a child, not a robot, has calendar functions for conversations related to different seasons and times of year or birthdays.
Diabetes detector
Mexican company Prosperia has developed an application that uses artificial intelligence to create databases whose algorithms detect if a person is at risk of developing diabetes.
Also, if you already have it, you can find out if there is a risk of complications.
This app has “risk calculatorsi.e. online questionnaires that collect information from patients in Prosperia data. From there, artificial intelligence is used to determine a person’s risk of suffering from a chronic diseasesuch as diabetes or hypertension.
Coffee with a look
The company Irisbond and the Azkoyan Group have created an automatic coffee machine that works with your eyes, thanks to advanced algorithms based on artificial intelligence and that allows the user to select the product they want without having to touch it with their hands, a solution which presents itself as ideal for helping prevent contagion amid the COVID-19 pandemic.
In Vitro Fertilization Doses
Researchers from the Eugin assisted reproduction and fertility group and the CSIC Artificial Intelligence Research Institute have developed an artificial intelligence algorithm capable of identifying the optimal dose of ovarian stimulation drug required by a patient in an in vitro fertilization cycle.
The model, developed by machine learning, prescribes with the same precision and reliability as a doctor, all thanks to an algorithm based on data collected from a sample of 2,713 patients and its performance has been validated with 524 additional patients, where the prescription of the model has been corroborated by the experience of specialists.
Comfortable heel shoes
Making high heels comfortable through the application of biomechanical research, neuroscience or infrared techniques is the goal of a pioneering research project developed by the Footwear Technology Center (Inescop), which aims to combine aesthetics and comfort.
The Taconshoe project studies how the curvature or break of a heel should be for the shoe to be comfortable at different heightssomething in which factors such as the deformation of the foot when climbing in a shoe with a high heel, the distribution of pressures on the metatarsal area and the toes or the alteration in the way of walking produced by this type of shoe, intervene .
Thanks to artificial intelligence and “big data”, a specific technology has been developed, a simulator of breaks or curvatures of the foot that allows it to be placed at different heights between 0 and 9 centimeters, in order to find the position that generates greatest comfort, after which the foot is scanned in 3D at the chosen height and the comfort parameters identified.
against child pornography
A team of researchers, in collaboration with Microsoft, has developed an artificial intelligence program in Germany who can distinguish child pornography from adult pornography with more than ninety percent accuracy to help the justice system.
In just one year, the working group in charge of this project managed to open some 1,600 procedures against more than 1,800 people thanks to the use of this tool. The objective is not to replace human and judicial expertise in child pornography cases, but to rapidly filter large amounts of suspicious materialwhich can help in investigations against pedophile networks.
Identify the Tiger Mosquito
Artificial intelligence is already identifying the tiger mosquito in photos submitted by citizens to the Mosquito alert app thanks to a ‘deep learning’ algorithm trained on 7,168 anonymous photographs received between 2015 and 2019.
This algorithm is able to correctly identifying 96% of tiger mosquito photographswhich will enable real-time detection of tiger mosquitoes on a large scale and faster control of this disease vector.
Researchers from Mosquito alert (belonging to CEAB-CSIC, CREAF and UPF) in collaboration with researchers from the University of Budapest have developed this artificial intelligence algorithm capable of recognizing the tiger mosquito (Aedes albopictus) in photos.
Jellyfish alert
A research team from University of Huelva and the Spanish Institute of Oceanography of Malaga has developed a model based on artificial intelligence and citizen science that anticipates the arrival of jellyfish on the beaches of the Costa del Sol.
With data collected through a mobile application and the use of a system that automatically detects and interprets user messages, experts predict the arrival of these marine species in bathing areas.
This research is part of a citizen science project, that is to say in which citizens are involved at one stage of the research process.
The chatbot that answers Don Quixote
Chatbots, artificial intelligence-based computer applications that can simulate a conversation with a person and provide responses automatically, have applications for a wide range of topics.
In this case we are talking about DulcineIAwhich answers all the questions and many more that a reader of Don Quixote might ask.
DulcineIA is a project developed by the company 1MillionBot with the support of the Ministry of Culture and Sports and the collaboration of the Cervantes Institute, which has already answered more than a thousand questions about the first part of Don Quixotefrom 1605.