MakerLab is a community of technology developers that work together with the goal of learning, teaching and sharing. Thanks to the support of the School of Science and Engineering and the CIDE PUCP, young students with a passion for technology gather to research on different technological advances, familiarize themselves with those topics, and then share that knowledge with the maker culture approach and the “learning by doing” methodology. On this occasion, we are conversing with Irina Avila, professor in our School and director of MakerLab PUCP.
What were the objectives for the 2018-1 semester?
On 2018-1, our main goal was to spread our methodology of active-collaborative learning to other study centers, strengthening our leadership. In this way, the members of our community have participated as technology mentors, promoting a creative experience and a learning through the application of technology in practical solutions. Likewise, they endorse a new way of studying and working: among peers, with no pressure and in a collaborative environment.
How important is it to keep encouraging initiatives like this one among students?
It is very important to introduce technology to students, with new strategies and methodologies that will prepare them to face this time of constant uncertainty, where technology advances are going beyond any predictions.
Students develop their projects in a relaxed and multidisciplinary environment. The general rule is “learn while doing”, without expecting many instructions, decreasing the pressure of getting it right at the first try, because everyone else is trying as well.
Not only do we promote the interest in learning about novel technologies, but also in offering solutions to problems that will be actually motivating to them. In this way, by having the opportunity of creating and developing solutions, they can contribute to a larger process.
The outstanding projects of 2018-1 MakerLab were:
“Student Analyzer”
Software to evaluate reading comprehension through a facial analysis, using “machine learning” to predict whether the reader has understood what (s)he has read. Keras library and OpenCV were used for image processing.
Developer: Luis Enrique Castillo, Mechatronic Engineering graduate from PUCP
“Agro Dron”
Optimization of a drone for farming, which goal is to identify the areas that need to be fumigates through image recognition.
Developer: Antonio Rujel, Mechanical Engineering from UNI.
System of playful learning of mathematics for kids between six and ten years using motion detector Kinect.
Developers: Piero Casusol, student of Mechatronic Engineering from PUCP and Diego Huarcaya, student of Systems Engineering from UPEU.
Robot capable of identifying and avoiding objects with artificial vision.
It utilizes Arduino and Python (OpenCV) to recognize objects.
Developers: Erich Balois and Teresa Lícito, students of Systems Engineering from UCV, Ramiro Chávez, student of Computer Systems Engineering from UPN.
Demonstration of Dijkstra’s algorithm, also called shortest path algorithm, using Open Street Map and Python.
Developers: Jhair Guzmán, student of Computer Engineering from PUCP and Pedro Placios, student of Engineering Physics from UNI.
Demonstration of the use of a personalized SteamVR plugin in Unity to track Virtual Reality controllers using only the gyroscopes
Developer: Carlos Felipe Rojas, student of Systems Engineering at UNI.