Three National University of Singapore (NUS) undergraduates have taken on an extra load to make campus life easier for their peers.
Using messaging app Telegram and their coding skills, they created a chatbot - College Laundry - that tells students when a washing or dryer machine is available and when their laundry is ready to be collected from the machines.
All the student has to do is download the messaging app and begin "chatting" with the bot using certain command words. The bot identifies the command word and "replies" with the relevant information.
"Sometimes we find that it's troublesome to go to the laundry room only to find that the machines are all in use," said 24-year-old Yong Shan Xian from the School of Computing. "We figured we could all communicate through a common chat."
The chatbot's other creators are 22-year-old Teo Wei Song, a life sciences student, and School of Computing student David Ten, 23.
They live on campus in Residential College 4, where College Laundry was in use by about half of the 600 students within a week of its launch.
They took two to three days to code the chatbot. Said Mr Yong: "Of course, that came with some compromise - like sleep."
While local universities have coding courses, self-initiated innovations like College Laundry are not common.
Associate Professor Ben Leong of the NUS School of Computing said coding the Telegram chatbot is simple, but the students' creativity was commendable. "I would give them an A for their initiative to want to do something useful for others," said Prof Leong.
Unlike other chatbots on the market which rely on the Internet for information - such as Siri, the voice-activated helper found on iPhones - College Laundry uses QR codes.
For example, when a student loads a washer or dryer, he takes a photo of a unique QR code on the machine and sends it to the chatbot. This tells the bot the machine is in use.
The same process applies when the student unloads the machine, freeing it up for someone else.
While there are no cases of user error yet, Mr Yong said someone using a machine without informing College Laundry would affect its effectiveness. The chatbot works best if everyone doing laundry uses it.
The trio are now looking into using sensors to detect whether a machine is in use - a similar concept used in smart home appliances currently on the market.
Response to the chatbot has been mostly positive, with six other residential colleges in NUS and a Nanyang Technological University residential hall asking to adopt it.
Two laundry companies have also expressed interest in integrating the chatbot into their machines, said Mr Yong.
"We hope this serves as an inspiration; that you don't need to find a big problem or money-making problem to solve. It can just be small problems that we see day to day."