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Artificial Intelligence to Identify Aquatic Plants in New Zealand

Water pollution has deteriorated due to rapid economic growth and increased urbanisation. Understanding water quality issues and patterns are also critical for water pollution reduction and regulation. To truly understand the quality of the marine ecosystem, most countries around the world have begun to develop environmental water management schemes.

Agriculture consumes 70% of freshwater today, with a utilisation efficiency of less than 50%. By reducing the amount of water used in irrigation, AI can help to streamline the use of water in agriculture. At the most basic level, AI systems can understand the water in the soil and estimate the water demand by considering crop growth-stage and managing sprinklers and drips. Advanced systems will be able to predict weather conditions, rain, humidity in the atmosphere etc and guide the sprinkler systems accordingly.

To meet the growing demand for IoT solutions from water utilities, telcos are expanding their capabilities by partnering with IoT platform vendors with water sector expertise. The next step in protecting Aotearoa New Zealand’s lakes and rivers from invasive aquatic weeds appears to be a combination of artificial intelligence and scientific ingenuity.

Management and detection of invasive submerged weeds cost millions of dollars annually, but National Institute of Water and Atmospheric Research (NIWA) researchers have developed a way to detect and identify submerged weeds. This technology will enable agencies to survey far larger areas more efficiently than is currently possible, and potentially lead to much faster responses to new incursions.

Submerged invasive weeds can degrade water quality, exacerbate silt and flooding, reduce the number of native animals and plants, and disrupt irrigation water delivery and hydroelectric power schemes. The National Institute of Water and Atmospheric Research (NIWA) developed a portable invasive species detector module that can be strapped to survey boats. The prototype is housed in a small waterproof case, complete with an underwater video camera. Inside is a computer with an artificial intelligence-based detector that has been trained to identify and log the locations of targeted invasive weed species in real-time.

Furthermore, NIWA’s principal technician has utilised a deep learning neural network – an artificial intelligence function – to train a computer model to recognise and record the GPS locations of two of New Zealand’s most invasive weeds, ‘lagarosiphon and hornwort’. These data can then be exported to a mapping programme to enable the implementation of control or eradication strategies.

“The deep learning process enables us to replace the human eyes and brain with a video camera and a computer by running a detection application that has been taught what to look for,” he said.

Training a detector requires a significant amount of computing power and can take days or even weeks depending on the complexity of the search environment and ‘target species.’ However, once trained, the trained detector is efficient and can be embedded in the computer inside the detector module for real-time detection.

The study is still in its early stages, and more fieldwork, data collection, and software development are needed to determine its true potential. However, according to a NIWA freshwater ecologist, early detection and prevention are critical for achieving effective freshwater biosecurity outcomes. The development of these detector modules will allow for rapid and cost-effective detection and mapping of large areas.

Currently, the majority of invasive species surveillance work is done by specialised divers. He also stated that the new technology has the potential to shift diver expertise from detection efforts to control strategy implementation.

Water quality modelling and prediction have played a pivotal and significant role in reducing time and consumption in lab analysis. Artificial intelligence algorithms were investigated as a potential alternative method for estimating and forecasting water quality.


Qlik’s vision is a data-literate world, where everyone can use data and analytics to improve decision-making and solve their most challenging problems. A private company, Qlik offers real-time data integration and analytics solutions, powered by Qlik Cloud, to close the gaps between data, insights and action. By transforming data into Active Intelligence, businesses can drive better decisions, improve revenue and profitability, and optimize customer relationships. Qlik serves more than 38,000 active customers in over 100 countries.


CTC Global Singapore, a premier end-to-end IT solutions provider, is a fully owned subsidiary of ITOCHU Techno-Solutions Corporation (CTC) and ITOCHU Corporation.

Since 1972, CTC has established itself as one of the country’s top IT solutions providers. With 50 years of experience, headed by an experienced management team and staffed by over 200 qualified IT professionals, we support organizations with integrated IT solutions expertise in Autonomous IT, Cyber Security, Digital Transformation, Enterprise Cloud Infrastructure, Workplace Modernization and Professional Services.

Well-known for our strengths in system integration and consultation, CTC Global proves to be the preferred IT outsourcing destination for organizations all over Singapore today.


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SIRIM is a premier industrial research and technology organisation in Malaysia, wholly-owned by the Minister​ of Finance Incorporated. With over forty years of experience and expertise, SIRIM is mandated as the machinery for research and technology development, and the national champion of quality. SIRIM has always played a major role in the development of the country’s private sector. By tapping into our expertise and knowledge base, we focus on developing new technologies and improvements in the manufacturing, technology and services sectors. We nurture Small Medium Enterprises (SME) growth with solutions for technology penetration and upgrading, making it an ideal technology partner for SMEs.


HashiCorp provides infrastructure automation software for multi-cloud environments, enabling enterprises to unlock a common cloud operating model to provision, secure, connect, and run any application on any infrastructure. HashiCorp tools allow organizations to deliver applications faster by helping enterprises transition from manual processes and ITIL practices to self-service automation and DevOps practices. 


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