Edama Organic Solutions received $780,000 USD seed investment from the KAUST Innovation Fund. KAUST has also signed a contract to build a commercial-scale composting facility for Edama on its Thuwal campus, with a recycling capacity of 5,500 tons. Edama will manufacture and sell products, including Edama Desert Compost and Edama Palm Peat. Why it matters: This initiative promotes sustainable waste management practices in Saudi Arabia by turning organic waste into valuable soil improvement products tailored for desert environments.
A research paper proposes a smart waste management system called TUHR for Makkah, Saudi Arabia, leveraging IoT and AI to handle waste accumulation during the annual pilgrimage. The system uses ultrasonic sensors to monitor waste levels and gas detectors to identify harmful substances, alerting authorities when containers are full or hazards are detected. The proposed system aligns with Saudi Vision 2030 by promoting sustainability and improving public health through optimized waste management.
Averda and KAUST have signed a 10-year contract to provide sustainable waste management solutions, targeting zero-waste goals by 2025. Averda will manage solid and hazardous waste, recycling, sorting, and disposal, building on a partnership since 2015 that has already recycled over 3,500 tonnes of waste. The new facility will include an all-electric fleet of waste collection vehicles and advanced sorting technology to divert waste from landfills. Why it matters: This partnership showcases a commitment to environmental sustainability and sets a precedent for technology-driven waste management solutions in Saudi Arabia.
Edama Organic Solutions, a KAUST startup, has opened a new organic waste recycling facility in the KAUST Research and Technology Park. The facility is the first of its kind in Saudi Arabia to use technology for waste processing and desert agriculture solutions. It will recycle 100% of KAUST's food and green waste, producing about 4,500 m3 of soil improver. Why it matters: This supports Saudi Vision 2030 by addressing environmental pollution and promoting sustainable agriculture in arid regions, aligning with the Saudi Green Initiative.
KAUST researchers have developed a technology to convert spoiled dairy and fruit beverages into valuable short-chain and medium-chain carboxylic acids (SCCAs and MCCAs). These acids can be used for animal feed, aviation fuel, and pharmaceuticals, with SCCAs valued at $300 per ton and MCCAs having 10x higher value. A pilot study is underway at KAUST, utilizing over 500 liters of waste per week from regional companies. Why it matters: This innovation supports Saudi Arabia's goal to eliminate 90% of landfill waste by 2040 and promotes a circular economy by transforming food waste into high-value products.
KAUST researchers are using black soldier fly (BSF) larvae to transform organic waste into protein-rich animal feed and high-quality organic fertilizer. BSF larvae consume organic matter and reduce waste volume significantly in a 12-day period. Organic Waste Management Solutions (OWMS), a startup launched by the team, is scaling up and commercializing the BSF-based process. Why it matters: This innovative approach offers a sustainable solution for waste management in the region, generating lower carbon emissions compared to existing technologies like incineration and landfilling.
KAUST and King Abdulaziz University (KAU) are collaborating to develop low-cost sodium-ion battery technology using fly ash, a waste material from burning fossil fuels. Researchers are purifying fly ash and using thermal treatment to engineer its structure for use as carbon electrodes in batteries. The resulting carbon electrode material is competitive with existing market products and can be used for other applications. Why it matters: This research offers a sustainable approach to energy storage by repurposing waste materials, potentially enabling cheaper and more environmentally friendly grid-scale energy storage for renewable energy sources.
MBZUAI researchers tackled the challenge of AI-powered waste detection in messy, real-world recycling facilities. They fine-tuned modern object detection models on real industrial waste imagery and combined this with a semi-supervised learning pipeline. Fine-tuning more than doubled performance and their semi-supervised pipeline outperformed fully supervised baselines. Why it matters: This research offers a practical path for open research that can rival proprietary systems while reducing the need for costly manual labeling in waste management, a problem of global importance.