The CSIRO’s Next Generation Graduates Programmes are industry-university partnerships aimed at developing a pipeline of home-grown, job-ready graduates to unlock the immense economic opportunity offered by AI and emerging technologies.
In this latest round, 14 programmes were funded, with RMIT leading four, including two by its Centre for Industrial AI Research and Innovation (CIAIRI), one by its Enterprise AI and Data Analytics Hub, and one by the Sir Lawrence Wackett Defence and Aerospace Centre. RMIT will also support a further three.
These programs will provide generous scholarships to domestic PhD students which allows them to be part of a multi-disciplinary team aimed at solving real-world challenges. The programmes are:
1. AI for Next Generation Food & Waste Systems (RMIT led, La Trobe supported)
This programme addresses the skills shortage in adopting advanced AI technologies in the areas of food and waste, a critical national manufacturing priority. This will boost food productivity, improve food quality control and logistics, reduce, and better manage waste generated during the life cycle of food production and consumption.
Through a range of industry-driven research activities, this program will produce a cohort of graduates that are not only equipped with practical AI skills but also ready to integrate into food and waste related industry sectors to generate real impact.
2. Developing Digital Capabilities to Support the Aged Care Sector (RMIT led, Victoria and Newcastle supported)
One of the recommendations in the Royal Commission into Aged Care Quality and Safety is to adopt technology to transform the aged care system so that carers’ time can be best used to deliver quality care. The report also recommended the use of technology to increase the connectedness of older Australians – to one another, families and carers, and to the broader community.
This programme aims to reimagine the role of technologies like AI, AR/VR and sensors which are critical in ensuring the sustainability of the sector. Our industry partners are driven by these challenges every day thus, the research undertaken in this programme will have great significance and impact.
3. AI Techniques for Emergency Management and Critical Infrastructure (RMIT led, Sydney Uni supported)
This programme will produce a cohort of graduates with much-needed skills in AI to support critical infrastructure and community safety. Some of the common AI techniques across the selected projects are:
- computer vision -creating 3D reconstructions from 2D images of interior designs and detecting potential hazards and threats via surveillance videos
- agent-based modelling and simulation (ABMS) – which is becoming increasingly popular to model and simulate the management of disaster events such as floods and bushfires and
- digital twin technology – which involves complementary approaches of digitising models of infrastructure, people, and business processes and one of the projects investigates the integration of all three aspects.
4. Applied AI and Digital Innovation for Defence and Aerospace Applications (RMIT led, Charles Darwin supported)
This programme will deliver graduates capable of tackling Australia’s pressing current and future challenges in the defence and aerospace sectors through the application of AI and digital technologies. It will expand opportunities for diverse communities of students and create workers skilled in emerging technologies, including applied AI, digital twins and threads, machine learning, robotics, cyber security, and modern manufacturing.
This interdisciplinary program builds on the strategic partnership between RMIT University and Charles Darwin University (CDU), which will see the creation of a joint Aerospace and Defence Industries 4.0 TestLab in the Northern Territory.
5. AI for Clean Energy and Sustainability (Monash led, RMIT supported)
Delivering clean and sustainable energy and enabling energy transition is a global challenge. AI is expected to play a significant role in this transition by enabling more effective models and tools, accurately predicting reliable supply, optimising maintenance and operations, making smarter decisions and assessing risk.
This programme will focus on the Recycling and Clean Energy National Manufacturing Priority to teach a variety of HDR students innovative AI technologies driven by these industry priorities.
6. Central Bank Digital Currency – Infrastructure & Applications (Macquarie led, RMIT and UTS supported)
A Central Bank Digital Currency (CBDC) would be a new digital form of money issued by the Reserve Bank. It could be designed for retail or general use, like a digital version of banknotes.
The development and deployment of robust, efficient and trusted CBDC requires the design, engineering, proving and integration of a suite of technologies including blockchain, security and privacy-preserving solutions and regtech (surveillance, alerting and compliance) technologies and the skilled graduates to help implement them.
7. Artificial Intelligence of Things Empowering Industrial Digital Twin (La Trobe led, RMIT and Swinburne supported)
This programme will develop new digital twin solutions powered by a combination of AI and the Internet of Things (IoT), to meet the needs of industry partners, seeking improved productivity and reduced maintenance and management costs.
By representing physical objects digitally, digital twins can harness real-time IoT data and optimise performance using AI and data analytics. Several research and industry challenges will be addressed, including accurate 3D modelling, digital twin model optimisation, reliable connectivity between the physical world and the digital world, and edge AI models.
Two tech companies operating within Hong Kong’s Smart Government Innovation Lab announced the roll-out of solutions that are now ready to be acquired by companies and institutions.
Solution I – Data collaboration (open data) platform with Privacy Computing
The company has developed a secure computing platform providing both data governance and AI capabilities, with which business partners could share data insights without data leakage to better promote their business/operation management. The platform was designed to enable other organisations like academic research institutions and start-ups to be nurtured to improve the information technology ecosystem in HK.
The solution was designed to be applied across the areas of Commerce and Industry, Education, Finance and Health as well as within a smart city.
The solution employs the latest in Artificial Intelligence (AI), Cloud Computing, Data Analytics, Deep Learning, Machine Learning, Natural Language Processing as well as Predictive Analytics.
By using the firm’s XDP secure computing platform, users can share data insights with others without data leakage concerns. Moreover, the data governance and AI capabilities of this platform help businesses and other institutions access alternative data, extract data insights for better decision-making as well as promote their businesses or operational performance either within industry or across industries. This, therefore, nurtures the economic ecosystem and academic development in HK. In addition, data sharing and collaboration also enhance researchers in the region further developing academic performance.
Solution II – Tunnel Vehicle Monitoring and Classification System via LiDAR and Video Camera
Manual tunnel monitoring is a time and resource-consuming process. The process is prone to human errors and miscalculations. Thus, the firm’s Tunnel Vehicle Monitoring and Classification system uses computer vision and 3D point clouds to derive insights from the video cameras and LiDAR sensors installed in the tunnels. It analyses the traffic in a tunnel, calculates the number of vehicles in predefined areas, determines the speed and direction of traffic, conducts vehicle classification (e.g., taxis, public buses, private cars), and displays real-time and accumulated statistics in a web-based dashboard, tailored to the user’s needs.
The solution was designed to by deployed across the areas of City Management, Infrastructure as well as Transport.
The solution employs the latest in Artificial Intelligence (AI), the Internet of Things (IoT) and Video Analytics.
This solution can help to improve the conditions of using tunnels by providing real-time tunnel usage statistics. The statistics can help users to understand the conditions of tunnel usage such as average speed of traffic, number of vehicles in queue and more.
In 2018, the Government established the Smart Government Innovation Lab to explore hi-tech products such as AI and relevant technologies, including machine learning, big data analytics, cognitive systems and intelligent agent, as well as blockchain and robotics from firms, especially local start-ups.
The Lab is always on the lookout for innovation and technology (I&T) solutions that are conducive to enhancing public services or their operational effectiveness. I&T suppliers are encouraged to regularly visit the Lab’s website to check on the current business and operational needs in public service delivery and propose innovative solutions or product suggestions to address them.
Singapore’s Agency for Science, Technology, and Research (A*STAR) and a consortium of businesses have unveiled BINgo, a smart bin whose prototypes will be initially deployed in three places, including AMK Hub, NEX, and FairPrice Hub and will there until 20 October 2023. BINgo uses artificial intelligence (AI), the Internet of Things (IoT), and smart sensors to help fix the wrong way Singaporeans recycle and the low number of people who recycle.
“The use of innovative manufacturing and artificial intelligence technologies in the development of BINgo will make it easier to identify recyclables and improve the efficiency of waste collection and sorting using automation,” says David Low, Executive Director of A*STAR’s SIMTech.
He also said that A*STAR is excited to co-innovate this solution and start this important pilot, which will help people in Singapore understand how important it is to recycle correctly and will try to increase the number of people who recycle.
BINgo wants to encourage people to recycle and increase the number of people who recycle by using smart sensors and AI-enabled automated sorting technology to improve the collection of recyclables like metal cans, glass, paper, and plastic packaging.
This means that when the trash is put into the machine, it can tell if the waste is recyclable or not and if it has any contaminants that might make it unsuitable for recycling, like leftover liquid and pearls in a half-empty bubble teacup.
As the user puts trash into the machine, the machine’s interface teaches them useful information about recycling.
In accordance with its commitment to promoting a circular and low-carbon economy, a group of businesses strives to develop reduce, reuse, and recycle programmes to avoid the usage of unneeded materials and the quantity of trash generated, particularly packaging.
A sustainability fund supported the development of BINgo, which was led by A*STAR’s Singapore Institute of Manufacturing Technology (SIMTech). The Sustainability Fund, which was established in 2019, intends to address sustainability and environmental concerns by increasing awareness, promoting creative ideas and projects, and establishing strategic partnerships.
SIMTech offered its knowledge in manufacturing technologies and product design and included AI, IoT, and smart sensor technologies in the prototypes to enable BINgo to sort recyclables autonomously.
With an easy-to-follow step-by-step guide and a user-friendly interface, BINgo is full of interactive and educational features that help shoppers tell the difference between recyclables and things that can’t be recycled. This lets them recycle more and do it right.
This design makes things work better and makes it easier to collect things, which makes things better for users. Also, the data on the waste that is collected over time will make it easier to tell which items can be recycled and make it easier to use statistics to better manage waste.
In addition, the group of companies has led other green plans, such as the “No Plastic Bag” plan, which requires supermarkets to charge for plastic bags. It also works to reduce food waste with a framework for waste reduction and is the pioneer partner for the BCA Green Mark Portfolio Programme.
Green Mark certification has been given to more than 40 stores. Two of its stores in Zhongshan Park and Kallang Wave Mall won platinum awards.
Two tech companies operating within Hong Kong’s Smart Government Innovation Lab have launched solutions that are now ready to be acquired by companies and institutions.
Solution I – IoT-Based Hazard Environment Alert System (iHEAS)
By using IoT Sensors, the iHEAS system collects, analyses, displays and disseminates local environmental conditions including temperature, humidity and water level over predefined areas. Environmentally hardened digital displays are used to provide critical environmental information and hazard warnings to the public.
The solution was developed to be applied in the areas of Climate and Weather, Environment, Recreation and Culture as well as Transport.
The solution employs the latest in Cloud Computing, Data Analytics, the Internet of Things (IoT) as well as Mobile Technologies.
Making use of outdoor IoT sensors for temperature, humidity and water level (flooding detection), etc., the solution collects critical data of a microenvironment like country park trails. The data is directed via an IoT network, e.g. LoRaWAN to a Cloud Computing Platform with rule-based analysis. Results are displayed on strategically placed outdoor, environmentally-hardened digital signage in condensed and easy-to-understand forms. Analytic reports are generated and disseminated to other B/D.
The technology provides the public with real-time, on-the-spot advice on the suitability (or unsuitability) of embarking on outdoor activities. It can be used as a deterrent should conditions prove undesirable. It prevents the over-ambitious undertaking of visits and minimises life-threatening incidents. In the medium term, it aims to reduce the reactive emergency rescue missions by Fire, Police and Flying Services and save emergency dispatches for people with real needs. It synergises the existing educational and alert systems of various government B/D.
Solution II – AIBOOSTER – Data Empowerment Platform
The AIBOOSTER solution is a collection of platforms that form an end-to-end ecosystem of data collection, data preparation, data mining and data visualisation. It works with existing business data to enable dataset management, data processing and update management. The platforms are as follows:
- AIBook is an auto-machine learning platform which supports automated modelling with zero coding. With an industry-leading algorithmic engine, the AI application process is simplified and intelligent transformation is facilitated.
- AIManager is a one-stop model hosting platform for rapid model deployment, prediction, monitoring and evolvement. It enables AI applications to boost business value.
- BI Canvas is a data visualization and analysis platform that integrates data connection, data transformation, visualization, and analytics functions into the end-to-end workflow.
The solution was designed to be applied in the areas of Climate and Weather, Commerce and Industry, Development, Education, Finance, Food, Population as well as Social Welfare.
The solution employs the latest in Artificial Intelligence (AI), Blockchain, Data Analytics, Deep Learning, Internet of Things (IoT), Machine Learning, Predictive Analytics and Robotic Process Automation.
AI+ Retail Solution
The AI+ Retail Solutions enables users to discover their business value and identify actionable insight in the data. The solution’s models help clients detect highly responsive customers for marketing campaigns. In real-world practice, model results enhanced the long-term conversion rate by 85%. The adoption of AI in marketing helps in building consumer relationships, enhancing the customer experience, and subsequently driving business values.
AI+ Meteorological Solution
This solution promotes the application of AI in weather forecasting and warning services to enhance the quality of weather services. The firm recently introduced deep learning and machine learning methods that use radar to predict future rainfall and predict AQI (Air Quality Index) values by using open data. AI Manager processes the big data with an iterative approach and generates simultaneous predictions to aid the forecasters in performing weather monitoring and making a final decision on forecasting.
AI+ Maintenance Solution
This solution uses AI to identify and prevent machine breakdowns before they happen. For example, vibration measurements are correlated with the data from different sources of sensors or IoT devices to gather system status information well beyond standard system maintenance needs. This enables predictive maintenance, in turn allowing industries to anticipate breakdowns and realise substantial operational savings.
Universiti Teknologi Malaysia (UTM) signed a Letter of Collaboration (LoC) on 2 September 2022 with a Malaysia-based technology company to enable collaboration in the field of Internet of Things (IoT), Communication Networks, Engineering and Technology.
The tech firm is a company that provides a solution provider of Systems Integration, Fibre Optic Sensing Solutions, Pipeline Integrity Monitoring Systems, Surveillance Systems, Fire & Gas Systems, High-Level Security Systems and the Internet of Things (IoT).
The collaboration between the two parties was started following the visit of the Ubiquitous Broadband Access Network (U-BAN) research team to the company’s office in Shah Alam on 2 December 2021. In the ceremony, UTM was represented by its Pro-Vice Chancellor of UTM Kuala Lumpur while the Chief Executive Officer represented the company.
The collaboration agreed upon by both parties covered the academic partnership and cooperation between UTM and the tech firm including the exchange of academic staff and students (undergraduate and postgraduates), Research and Development (R&D) in Communication Technology as well as Internet of Things (IoT), joint seminar/conferences and the co-supervision of postgraduate students.
In his statement, the Pro-Vice Chancellor of UTM Kuala Lumpur after the signing ceremony said that with the joint venture, the relationship and cooperation between UTM and the firm will hope to grow stronger and last longer and will succeed in providing high-impact results to both parties. The Pro-Vice Chancellor also acknowledged the firm’s representatives for making this cooperation possible.
The positive discussion opens opportunities for research collaboration such as industry grants and human capital development. The cooperation that will be established can improve the reputation of joint research with industry at the national and international levels, he added.
In 2020, the growth of Malaysia’s digital economy was accelerated by the COVID-19 pandemic which gave rise to new digital businesses, forced traditional brick-and-mortar enterprises to pivot online, and saw millions of Malaysians go virtual for their eCommerce, entertainment, and even education needs.
The delivery of quality education now is dependent on a student’s home broadband connectivity, or access to laptops or computers. To ensure that no Malaysian is left behind to catch the wave of digitalisation, the government is laying the foundation for the region’s transformation towards an advanced digital economy. This foundation includes building the infrastructure, facilitating innovation, and creating an ecosystem for all of us to contribute to bringing forth higher standards of living, the fruits of which will be enjoyed by all Malaysians.
MyDIGITAL outlines the plans to accelerate Malaysia’s progress as a technologically advanced economy, through the Malaysia Digital Economy Blueprint. This will chart the path to strategically position ourselves as a competitive force in this new era.
MyDIGITAL was developed to help realise the nation’s Twelfth Malaysia Plan, 2021-2025 (RMKe-12), as the government works on Wawasan Kemakmuran Bersama 2030. In facing this digital economy transformation, it is imperative to collaborate and take the necessary steps to adapt and collaborate for the next normal. The journey is not going to be easy but under unprecedented circumstances, we need to be brave enough to make this quantum leap forward to elevate the quality of life for all Malaysians.
Research institutes under the Ministry of Industry and Trade (MoIT) have been researching and commercialising cutting-edge technologies, including applications based on the Internet of things (IoT), artificial intelligence (AI), cloud computing, big data, blockchain, 3D printing and robotics.
MoIT’s institutes plan to strengthen their science and technology research activities to develop key industries as well as promoting smart production and digital transformation, as per the trends of the 4.0 industrial revolution.
A MoIT press release quoted the Director of the Vietnam Research Institute of Electronics, Informatics and Automation (VIELINA) as saying that the institute had researched and mastered several background technologies of industry 4.0 before the concept was introduced in Vietnam. Now, it hosts quite a few advanced products such as an integrated control system for underground coal mines, product quality external inspection systems using AI and machine vision that is being applied in some foreign-invested enterprises and an automatic feed control and ventilation system for dairy farms using IoT technology.
Most recently, VIELINA manufactured a synchronous automatic control monitoring system for tea production and processing, which is currently in operation at a private facility in the Lai Chau province. This is the most modern large-capacity (producing 50 tonnes of fresh tea per day) tea production line operating in Vietnam. It is worth mentioning that the system was designed, manufactured, and installed by Vietnamese experts, in which the most important stages were 100% automated thanks to applications of AI and IoT, the Director explained.
For an industrial machinery and instruments company, the institute manufactured a smart goods loading and unloading system in its warehouses based on the application of industrial robots. This system has been commercialised for many fertilizer and animal feed production units with costs 40%-60% lower than those of imported products. Additionally, the institute proposed and put into practice a number of technological solutions for the logistics activities of small and medium-sized enterprises (SMEs) in Vietnam.
MoIT manages a network of 13 research institutes, two of which have been equitised (excluding research institutes under economic groups and corporations, and science and technology organisations at universities and colleges under the ministry). In general, the institutes’ sci-tech activities have made positive contributions to the innovation level of enterprises in the industry and trade sectors. Many research products of these projects have been effectively applied to production and business in enterprises, contributing to improving their production capacity, quality, and competitiveness.
In May, MoIT, the People’s Committee of Vinh Phuc province, and a private electronics company launched a smart factory development project in the northern province of Vinh Phuc that aims to train 100 Vietnamese experts and provide consultation to help 50 businesses set up smart factories in 2022 and 2023.
As OpenGov Asia reported, consultants would be trained for 12 weeks to improve their knowledge and skills in setting up smart factories. The smart factory cooperation project is part of a series of innovative consulting activities for Vietnamese businesses and training experts to strengthen industry development activities.
Through the application of emerging technologies in production and manufacturing, businesses can improve their productivity and product quality, and reduce production costs. The project is expected to help SMEs improve the provision of supporting products and meet the production requirements of large corporations, gradually joining regional and global supply chains.
The Health Sector Cybersecurity Coordination Centre (HC3) of the U.S. Department of Health and Human Services (HHS) released an advisory for the healthcare industry regarding the risks posed by using the Internet of Things (IoT) gadgets and urging it to be proactive in addressing such security dangers.
In particular, the HC3 supplied a listing of the maximum commonplace IoT assaults and pointers for minimising dangers hindering IoT devices, which consist of:
- converting default router settings;
- the use of unique passwords on every tool;
- warding off the usage of typical plug-and-play;
- retaining both software and firmware up to date; and
- implementing a zero-trust model.
The HC3 also cited the importance of IoT security. Any internet-connected gadget is susceptible to hacking, and the IoT is no exception. A breach of these devices could result in catastrophic consequences, including tampering with traffic lights, disabling home security systems and harm to human life.
Since these devices might gather data, including personally identifying information, it is crucial to protect these systems. The ultimate objective is to protect the entire system, however, there are steps that may be taken to help achieve this, including securely storing, processing, and transferring data; maintaining the device’s security; and updating the device to lessen its vulnerabilities.
With the installation of IoT technology in an organisation, users also increase the attack surface upon which they can become a target for malicious activities. A flat network is one that contains IoT, IT devices, and operational technology (OT) in the same network.
Once attackers get initial access, they can execute the lateral movement and infiltrate more sensitive systems; this is the primary vulnerability. Network segmentation is an effective method for reducing the attack surface and preventing the compromising of entire systems.
The purpose of network segmentation in cyber security is to prevent the transmission of malware to other OT and applications. In network segmentation, the network is divided into several subnetworks or zones, which can minimise congestion and limit failures. This isolates the IoT devices from other IT equipment in use. Without segmentation, organisations run a greater risk of being hacked.
Some of the common IoT attacks are Privilege Escalation wherein an attacker can exploit bugs, unpatched vulnerabilities, design flaws, or even operating systems in an IoT device to obtain unauthorised access.
There is also a Man-in-the-Middle (MITM) Attack. This is a type of attack where the attacker can intercept information being sent between two parties and can also be used to steal or alter data.
The term Eavesdropping is when an attacker intercepts, deletes or modifies data that is transmitted between devices. This attack relies on unsecured network communications, while the Brute-Force Attacks aim to gain access to the IoT devices that are left unchanged with factory-set passwords.
Similarly, in Firmware Hijacking attackers can take advantage of this environment by adding fake updates or drivers to download malicious software.
Distributed Denial-of-Service (DDoS) Attack is when infected with botnet malware, IoT devices can be used to perform large-scale cyber-attacks. On the other hand, the Physical Tampering Attack is when the attacker could gain initial access from physically insecure IoT devices to install malware.
Meanwhile, the U.S. Cybersecurity and Infrastructure Security Agency (CISA) and the Ukrainian State Service for Special Communications and Information Protection (SSSCIP) have signed a Memorandum of Cooperation (MoC) to increase collaboration on common cybersecurity goals.
The MOC strengthens CISA’s current connection with the Ukrainian government in the areas of statistics exchanges and sharing of high-quality practises on cyber incidents, technical exchanges on the security of critical infrastructure, cybersecurity education, and cooperative athletic activities.
Tech companies operating within Hong Kong’s Smart Government Innovation Lab announced the roll-out of solutions that are now ready to be acquired by companies and institutions.
Solution I – Website Extraction Solution
Regardless of their size, for all businesses, scraping the web for data to fuel their market research efforts offers the broadest and most insightful perspective of their respective industry. Manually acquiring data for market research is a mundane, arduous task – one, fortunately, easily automated by intelligently designed web crawlers.
To this end, a company under HK’s Smart Government Innovation Lab has developed a Website Extraction Solution that converts unstructured website data into structured ready-to-consume data. In this solution, a self-built data automation platform (called DataCanva) has been developed to scrap website information automatically, continuously and effortlessly, perform various data transformations and then output structured data ready for consumption through files, APIs and webhooks.
The Website Extraction Solution has a number of proprietary technologies to enable data crawling at scale even on difficult sites:
- Anti-ban: the technology has strategies to emulate a human visit session to avoid banning.
- Auto-queuing: Some sites have implemented auto queuing features but when the sites are overloading, this technology will enable the crawlers to queue up in a virtual waiting room just like a human.
- Login: While some sites require a valid credential and some session-related mechanics in order to load more data, the technology works seamlessly in these scenarios.
- Deep crawling: the technology does not only target web pages but also attachments such as WORD and PDF files.
- Natural Language Analysis: the technology can extract key phrases, key sentences and perform summarisation if needed.
- Data Change Detection: the technology extracts delta changes in data to minimise the data crawling workload and allow timely feedback.
- Rotational Proxy: the technology leverages a large pool of IP to decrease latency and improve success rate.
- Screen capture: the technology saves the screen in a PDF file for a historical snapshot of the website for future review.
The solution was developed to be applied in the areas of Broadcasting, City Management, Climate and Weather, Commerce and Industry, Development, Education, Employment and Labour, Environment, Finance, Food, Health, Housing, Infrastructure, Law and Security, Population, Recreation and Culture, Social Welfare as well as Transport.
The solution uses the latest in Artificial Intelligence (AI), Cloud Computing, Data Analytics, Deep Learning, Machine Learning, Natural Language Processing as well as Predictive Analytics.
The Website Extraction Solution is suitable if the below use cases:
- Market trend analysis
- Price monitoring (e.g., on major E-commerce websites)
- Research and development
- Competitor analysis
- News/alerts monitoring (i.e., good for compliance monitoring)
- Profile analysis (i.e., retrieve data to enrich the user/company profile)
Solution II – Things of Artificial Intelligence (ToAI)
ToAI is a unified platform that helps collect and prepare the data, builds, trains and deploys users’ ML models and monitors and automatically retrains them, offering performance at speed.
The solution was designed to be applied in the areas of City Management, Climate and Weather, Environment, Health, Housing, Infrastructure as well as Transport.
The solution uses the latest in Artificial Intelligence (AI), Data Analytics, Internet of Things (IoT) as well as Machine Learning.
Smart Equipment – the solution provides an Internet of Things (IoT) platform to connect various sensory devices installed on different equipment, to monitor operation conditions and improve safety, efficiency, effectiveness and endurance.
Airconditioning Energy Optimisation – the solution also provides an Internet of Things (IoT) platform to connect various sensory devices installed across the office workspaces, to monitor and optimise aircon cooling operations.