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ATTRACT student projects
Discover the ATTRACT student projects boosting sensing and imaging technologies to enable breakthrough innovations for society
Team
The team members working on this project are the following:
Juliane Hanna
Barbara Bopp
MSc in Business Analytics
Esade Business School
Xueyin Gao
MSc in Business Analytics
Esade Business School
Ebrahim Abu-Helalah
Master on Telecommunication Engineering
UPC
Roser Batlle
Master on Telecommunication Engineering
UPC
Jeroen Robert
Ernst
Service design
IED
Marilza dos Santos
Freire
Virtual reality
IED
Project Sniffdrone
is based on ATTRACT project Sniffdrone
Background
SNIFFDRONE is centred on improving current odour assessment methodologies in wastewater treatment plants by creating a drone with olfactory capabilities, able to provide odour measurements and locate the source of malodours autonomously, leading to a substantial improvement in plant management.
The goal of the project carried out in Technology for Social Innovation (TeSI) consisted of the exploration of alternative areas of application for the SNIFFDRONE, along with the development of one of these identified possibilities. Furthermore, the team was tasked with expanding and describing the specifications for the identified application and to create a business model proposal for the resulting product.
Outcome
The research for this project has identified various possible areas of application for the SNIFFDRONE that have a positive social and environmental impact. The main identified area of application outlined in this document is for the detection of forest fires, as forest fires are becoming an increasingly pressing social and environmental problem due to climate change.
Taking into account the context outlined in previous sections and the rising trend of electronic noses in fire detection, it is believed that this field is innovative and disruptive, but at the same time feasible.
On the other hand, alternative applications for the SNIFFDRONE might be easier and more straightforward to implement due to shared points with the wastewater treatment plant application that the SNIFFDRONE was primarily developed for.
The most promising sectors identified for drone-based implementations are agriculture and industrial plants. In conclusion, prototype testing in a natural environment is required to test the suitability of the SNIFFDRONE for the detection of forest fires and to ultimately validate this application.