<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[Baram school wins national STEM title with AI-guided waste sorting project]]></title><description><![CDATA[<p dir="auto"><strong>A school-cleaning task became the basis of SMK Long Bedian's winning national STEM project: a camera identifies waste, then opens the bin for the appropriate category.</strong></p>
<p dir="auto">The Baram school took first place at the Petrosains Tech4All 2026 National Level Competition in Kuala Lumpur on October 12, DayakDaily reported from the organiser's release. The competition was held at Petrosains, The Discovery Centre—not at the school in Sarawak.</p>
<p dir="auto">Called S.O.R.T., the project combines Arduino coding, a camera and AI tools including Teachable Machine to distinguish cans, plastic and paper. Its stated purpose is to make sorting easier for the school's cleaner while helping students practise waste separation.</p>
<p dir="auto">That is a practical school prototype, not evidence that an automated recycling system has been rolled out across Baram. The report gives no tested accuracy rate or wider deployment plan, so the award should not be read as a claim that the system can identify every type of rubbish.</p>
<p dir="auto">The national competition brought together 40 students and 20 teachers from ten schools across six states. For Sarawak's STEM learning, the distinctive result is the use of coding and image recognition on a familiar local task, rather than technology presented only as a classroom exercise.</p>
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