Students of Computer Science, Cyber Security and Software Engineering Department of
Caleb University Imota, in Lagos, have emerged champions at the Bells University of Technology Hackathon competition.
This is contained in a statement by Mr Olawale Adekoya, Information, Media and Publication Specialist, issued to newsmen in Lagos.
According to the statement, the Acting Vice Chancellor of the university, Prof. Sunday Adewale, while hosting the victorious team in his office, declared that the institution has become a colossal hub for innovation and academic excellence.
“The team emerged champions courtesy its newly developed world class software named ‘Valor’
“It is a stunning demonstration of creativity and technical prowess,
“Valor, the smart, bold, brainy, savvy, Mango Master”, that won the first position for Caleb university, fuses artificial intelligence power with fruity precision, using advanced computer vision and deep learning models, thereby detecting ripeness in a snap.
“It was strategically designed to leverage machine learning algorithms and image processing, as it classifies ripeness with impressive precision.
“Composed of skilled student professionals in software engineering, data science and artificial intelligence (AI), the students’ innovative solution, fuelled by the power of vivid imagination, addresses common challenges in the agricultural sector, as the team developed a state-of-the-art app that utilises machine learning and AI to detect whether a mango is ripe or rotten,” the statement said.
It noted that the professor of Apllied Mathematics added that the success of Valor at the Bells university Hackathon competition, was a testament to Caleb university’s commitment to nurturing academic excellence, innovation and real-world problem solving endeavours.
“This is a testimonial of the hard work we do in our classroom.
“As an institution, Caleb university fosters an environment that emphasises interdisciplinary collaboration.
“It also enhances hands-on learning and cutting-edge research, providing students with the tools and resources necessary to succeed in today’s rapidly evolving technological landscape,” the statement said.
According to the statement the Team Valor worked tirelessly to develop a product that not only highlighted their technical expertise, but also provided a practical, market-ready solution for the agricultural industry.
It added that the Head of Department, (HOD) Dr Adeniyi Akanni and team Coordinator, Mr Theophilus Ajala, both said the team’s winning product was a sophisticated web and mobile application that leveraged advanced machine learning and AI algorithms.
“This App can accurately determine the ripeness of mangoes by analysing images and data.
“Indeed, the team’s pioneering work represents the intersection of technology and agriculture.
“The AI-powered mango ripeness detection App, is not only a testament to technical expertise, but also a symbol of the power of interdisciplinary collaboration.
“As they continue to enhance their project, Caleb university has proven to be the destination for advancing agricultural and scientific innovation, setting new standards for how technology can improve food quality and reduce waste worldwide, it quoted them.
On his part, the team lead,Harmony Abayomi, a student of Computer Science, said detecting ripeness and spoilage in mangoes remained a significant challenge for farmers, suppliers and consumers.
“Identifying when a mango is perfectly ripe can be difficult.
“Overripe fruits lead to wastage and loss of value, while under ripe ones fail to meet the expectations of consumers who want fresh, ready-to-eat and nutritious fruits.
“The importance of this App becomes expedient when one feels that traditional methods, like visual inspection or physical feel, are often subjective and unreliable, which may result in good fruits being discarded or left unsold,” he said.
The statement added that apart from the team Valor, the second group, named Team Sputter, also developed a super application, named ‘Sputter’.
It noted that the Sputter was capable of detecting fake news.
