KUALA LUMPUR, 8 April 2026 – In conjunction with the UTM Vice-Chancellor Engagement Session (April 2026), the Centre for Artificial Intelligence and Robotics (CAIRO), Universiti Teknologi Malaysia (UTM) has developed KenalKayu, an automated system for tropical timber species identification using image processing and Artificial Intelligence (AI) technologies.
The project is led by Dr. Ts. Uswah Khairuddin (UTM) and represents a collaborative effort involving Assoc. Prof. Ir. Dr. Anis Salwa Khairuddin (Universiti Malaya), Azlin Ahmad (Universiti Teknologi MARA), and Nenny Ruthfalydia Rosli (UTM). The system is developed to enhance the efficiency and accuracy of timber species identification, which traditionally relies heavily on human expertise.
Malaysia is home to more than 1,000 tropical timber species and has a well-established timber industry that contributes significantly to the national economy, creating a strong need for a more systematic, reliable, and efficient timber species verification system. Conventional identification methods require intensive professional training of approximately two to three years to achieve expert-level competency, resulting in a high dependency on skilled personnel and posing challenges in terms of time, cost, and operational efficiency, particularly in field environments.
As a solution, KenalKayu enables automated timber species identification in less than one second, significantly improving efficiency while reducing reliance on human expertise. The system operates through several key stages, beginning with wood image acquisition, followed by image processing, texture feature extraction, and finally species classification using Artificial Intelligence (AI) algorithms.
KenalKayu is designed to support practical deployment in real-world environments. It features real-time automated identification, a portable and field-ready design, and supports both online and web-based usage. In addition, the system is integrated with a verified timber species database sourced from the Forest Research Institute Malaysia (FRIM), further enhancing the accuracy and reliability of identification results.
The development of KenalKayu is expected to enhance operational efficiency and productivity within the timber industry while reducing dependency on expert personnel. The system also supports industrial applications, research activities, and enforcement efforts, particularly in field operations. Furthermore, it strengthens the adoption of Artificial Intelligence in natural resource management.
CAIRO, UTM envisions that this innovation will contribute to a more sustainable and competitive timber industry, while reinforcing its position as a leading centre in AI and robotics innovation.
This innovation is part of a series of AI-driven solutions developed by CAIRO, Universiti Teknologi Malaysia (UTM). Stay tuned as more impactful projects will be introduced in upcoming releases.
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