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Canadian University Dubai Students Create Smart Garbage Bin
The AI-driven household waste sorter uses “social robotics” to improve refuse management.
Canadian University Dubai (CUD) students have developed an innovative solution for sorting household waste. The system uses artificial intelligence, mechatronics, and so-called “social robotics” to swiftly and accurately sift through garbage. Known as the Social Robot Garbage Classifier, the project is a collaboration between students from the School of Engineering, Applied Science and Technology, and the Department of Public Health.
The idea for the smart garbage bin was formulated initially by Computer Network Engineering major Jehad Al Jaghoub, who explained, “Often people will not sort recyclable materials, or will accidentally place items in the wrong bin. Our goal is to improve the outcome of recyclable garbage sorting and, ultimately, to see these smart bins installed across Dubai. The mechatronics system uses sensors, allowing the robot to interact with users and understand their waste disposal needs. Precision-engineered actuators then translate this input into actions, ensuring that trash is correctly sorted and discarded”.

Co-creator and Public Health major Abdullahi Suleiman added: “The camera-based waste detection system uses advanced image recognition algorithms to identify items swiftly and accurately, enabling bottles, cans, and other recyclables to be identified with remarkable precision. This advanced system minimizes errors, guaranteeing that waste is accurately sorted and disposed of, significantly contributing to sustainable waste management”.
The university students’ prototype waste management system will soon compete in two regional innovation competitions, including the Institute of Engineering and Technology GCC Robotics Challenge, which showcases solutions for socially interactive robotics.
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The students are supported in taking their creation to competitions by CUD Assistant Professor Dr. Salih Rashid Majeed, who summed up the project by saying, “This smart garbage bin is a remarkable innovation at the intersection of social robotics and mechatronics system design and represents the university’s strategy to harness the power of artificial intelligence to deliver sustainable practices. The social aspect of the robot creates an intuitive and user-friendly waste disposal experience that has the potential to reshape waste management as we know it”.
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ESET Bets On Specialized Security AI At 0.5% The Training Cost
ESET says NeoCortex can estimate an attacker’s next move, with a kill switch and human oversight built in to keep it from going rogue.
A sign-in anomaly, a suspicious process launch and an unusual connection may look harmless alone. Together, they can describe an intrusion that is hard for security to teams to piece together.
To solve that problem, ESET announced ESET NeoCortex on November 4, 2026: a specialized foundational AI model for cybersecurity. It powers ESET LiveCortex, available within the ESET PROTECT Platform, which connects fragmented security signals and turns them into actionable incidents.
Filtering is the main selling point, with LiveCortex processing billions of raw telemetry events daily, and just 0.00111% of them contributing to incidents presented to customers. The aim is less alert fatigue and more analyst time spent on threats that matter.
NeoCortex is built on world-model architecture, learning how digital environments behave and how events relate. ESET says that lets it reconstruct missing incident context, recognize similar past cases and estimate an attacker’s likely next step – what the company calls “minus-one-day defense,” a chance to intervene before the next stage unfolds. ESET points to Black October, the week leading up to October 25, 2026, when critical security issues affecting PHP, Linux, GitLab and other key systems demanded rapid, prioritized responses, as the kind of moment where that context matters.
ESET’s internal research also suggests a specialized model like NeoCortex can be trained at up to 200 times lower cost than a large general reasoning model, while delivering more accurate, defense-focused results. The company credits optimized training, a focus on cybersecurity vocabulary, lower computing requirements and privately owned hardware.
Also Read: Dubai Says Its Deepfake Detector Needs Just 7 Seconds Of Video
“AI is accelerating both cyberattacks and cyberdefenses. With ESET NeoCortex, we are applying our AI investment to develop specialized foundational cybersecurity intelligence that remains under our control and strengthens, rather than replaces, human expertise,” said Juraj Malcho, Chief Technology Officer at ESET.
As part of the design, NeoCortex forms part of a layered architecture combining specialized models, deterministic controls, correlation logic, validation, auditability and expert human oversight. Safeguards include restricted sandboxes, read-only tools, continuous monitoring, defined usage and token limits, a kill switch and human oversight of critical response decisions. The model is also developed and self-hosted on ESET’s own infrastructure, which the company says reduces exposure to shifts among third-party AI providers, including commercial and geopolitical ones.
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