Oman

ECOTHON tackles pressing environmental issues

First prize of RO 1,500 went to team SUST comprising Hamed al Masroori, Abdelrahman al lam and Ilyas al Numani for their project that took up the challenge of waste.
 
First prize of RO 1,500 went to team SUST comprising Hamed al Masroori, Abdelrahman al lam and Ilyas al Numani for their project that took up the challenge of waste.

MUSCAT: ECOTHON 2026, which was held as part of Oman Climate Week 2026, brought together 150 participants to tackle real-world environmental issues.
Dana al Zadjali, Project Manager of the hackathon, aljabr, said, 'We have had 20 teams participating, and the age group ranged between 19 and 40. The hackathon focused on issues of climate change such as microplastic pollution, cooking oil, food waste, etc. The teams also attended workshops and mentorship. Finally, they presented their prototypes to the panel of judges.'
The ECOTHON was supported by Oman LNG, aljabr, Al Sharqiyah South Governorate and the Environment Authority.
The three-day intensive climate innovation hackathon focused on two main tracks with six core prompts: Track 1 (General): Food waste and GHG emissions, cooking oil, and microplastic pollution. Track 2 (Plant-Related): Oil remediation in contaminated soil, methane quantification at intermittent vents, and dynamic fugitive monitoring.
Teams received hands-on mentorship from industry experts before pitching their final solutions to a judging panel for top positions and monetary prizes. Promising projects also secured ongoing support from Oman Energy and Al Jabr to explore viable startup creation.
First prize of RO 1,500 went to team SUST comprising Hamed al Masroori, Abdelrahman al lam and Ilyas al Numani for their project that took up the challenge of waste: Oman generates two million tonnes of municipal solid waste a year (150 Mt across the GCC), with 70 per cent of recyclables lost and 80 per cent going straight to landfill.
Their solution was an AI-vision-driven adaptive conveyor system (running on Jetson Nano, ROS 2-controlled arms) that sees, classifies, and separates waste in real time, self-learns weekly on Gulf-specific data, and targets 95 per cent recovery purity with a 55 per cent cut in labour needs.
The second winner was Emissiq AI with team members Wameedh al Dhuli, Yuma al Hasani, Maryam al Maskari, Mohammed Azharruddin, and Madiha Kazim, and they won RO1,000. Their challenge was methane quantification at intermittent vents, and their solution: EMISSIQ's solution took the incomplete, intermittent data that existing monitoring systems capture and reconstructed it into full emission events — figuring out which equipment caused the leak, quantifying how much methane was released (with uncertainty bounds), predicting risk, and ranking which sources need urgent attention. Instead of treating every alert equally, it lets operators focus on the highest-impact leaks first. The result is fewer recurring methane losses, less wasted natural gas, more efficient maintenance, and real environmental and business value pulled out of monitoring infrastructure operators already in place.
Third place went to Cellova comprising Mohammed al Kwai, Ameer al Badi, Waleed al Aghbari, Sheikah al Khaduri and Aysha al Kaabi.
Their challenge was food waste and GHG emissions. They received RO 500 Cellova tackled the waste created when agricultural and plant residues are burnt, dumped, or left unused — a practice that drives greenhouse gas emissions and squanders a valuable resource. Their solution converts locally sourced plant waste into nanocellulose and its byproducts (cellulose, hemicellulose, and lignin), turning it into high-value input material for more than 13 industries. This closes the loop on a circular economy, cuts environmental harm, and offers a sustainable substitute for conventional materials.