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Ecosystm Insights - Page 7 of 79 - A new age Technology Research platform to help you access latest market insights,expert opinions and research data
Making Concrete Change: Strategies for Carbon Reduction in Urban Development

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Despite an increase in energy efficiency investment, the construction sector’s energy consumption and CO₂ emissions have rebounded to an all-time high. Buildings currently contribute 39% of global energy-related carbon emissions – 28% from operational needs like heating and cooling, and 11% from construction materials.

In the next three decades, with the global population expected to reach 9.7 billion, the construction industry will face the pressure to meet growing infrastructure and housing demands while adapting to stricter environmental regulations.

The urgency of climate action demands that governments mandate low-carbon practices in urban development.

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Click here to download ‘Making Concrete Change: Strategies for Carbon Reduction in Urban Development’ as a PDF

Increase Use of Low-Carbon Materials

Traditional building materials like concrete, steel, and brick are strong and durable but environmentally costly. This high embodied carbon footprint is prompting a shift towards low-carbon alternatives. Indonesia is using ‘green cement’ – made using environmentally friendly materials – in the development of its new futuristic capital Nusantara. This has led to an estimated reduction in carbon emissions of up to 38% per tonne of cement so far.

Nordic countries are setting ambitious targets for low-carbon materials. Starting in 2025, Finland will require life cycle assessments and material declarations in construction to reduce emissions, detailing building components and material origins. Denmark is also prioritising low-carbon materials through energy-efficient designs, sustainable materials, and stringent building codes.

Mandate Whole-Life Carbon Emission Assessments

Whole Life-Cycle Carbon (WLC) emissions encompass all the carbon a building generates throughout its lifespan, from material extraction to demolition and disposal. Assessing WLC gives a comprehensive understanding of a building’s total environmental impact.

The London Plan is a roadmap for future development and achieving the goal of a zero-carbon city. The plan includes provisions for WLC analysis, specific energy hierarchies, and strategies to reduce London’s carbon footprint.

With a bold vision of a fully circular city by 2050, the Amsterdam Circular Strategy 2020-2025 lays out a comprehensive roadmap to achieve this goal. Key elements include mapping material flows to reduce reliance on virgin resources and mandating WLC assessments.

Enforce Clean Construction Standards

From green building codes to tax incentives, governments around the world are implementing innovative strategies to encourage sustainable building practices.

The Philippines’ National Building Code requires green building standards and energy efficiency measures for new buildings.

Seattle offers expedited permits for projects meeting embodied carbon standards, speeding up eco-friendly construction, and reinforcing the city’s environmental goals.

New Jersey offers businesses a tax credit of up to 5% for using low-carbon concrete and an additional 3% for concrete made with carbon capture technology.

Promote Large-Scale Adaptive Reuse

Large-scale adaptive reuse includes reducing carbon emissions by making existing buildings and infrastructure a larger part of the climate solution.

London’s Battersea Power Station restored its iconic chimneys and Art Deco façade, transforming it into a vibrant hub with residential, commercial, and leisure spaces.

The High Line in New York has been transformed into a public park with innovative landscaping, smart irrigation, and interactive art installations, enhancing visitor experience and sustainability.

Singapore using adaptive reuse to rejuvenate urban and industrial spaces sustainably. The Jurong Town Corporation is repurposing a terrace factory for sustainable redevelopment and preserving industrial heritage. In Queenstown, historical buildings in Tanglin Halt are being reused to maintain historical significance and add senior-friendly amenities.

Establish Circular Economy

As cities worldwide start exploring ways to go circular, some are already looking into different ways to leverage innovative practices to implement circular initiatives.

Toronto is embedding circular criteria into procurement by requiring circular economy profiles, vendor action plans, and encouraging circular design for parklets. The city also recommends actions for transitioning to a circular economy and is developing e-learning on circular procurement for staff.

Japan uses Building Information Modeling to optimise resource consumption and reduce waste during construction, with a focus on using recycled materials to promote sustainability in building projects.

Adopt Electric Vehicles

The share of EVs increased from 4% in 2020 to 18% in 2023 and is expected to grow in 2024. This trend reflects a global shift toward cleaner transportation, driven by technological advancements and rising environmental awareness.

The Delhi EV Policy aims to expand charging infrastructure and incentives, targeting 18,000 charging points by 2024, with 25% EV registrations and one charging outlet per 15 EVs citywide.

Singapore is adopting EVs to reduce land transport emissions as part of its net-zero goal, aiming to cut emissions by 1.5 to 2 million tonnes. The EV Roadmap targets cost parity with internal combustion engine (ICE) vehicles and 60,000 charging points by 2030.

Australia has set new rules to limit vehicle pollution, encouraging car makers to sell more electric vehicles and reduce transportation pollution.

Promote Circular Economy Marketplaces

Circular marketplaces play an important role in the new economy, changing the way we use, manufacture, and purpose materials and products.

The UK’s Material Reuse Portal aggregates surplus construction materials post-deconstruction, offering guidance and connections to service providers. It integrates with various data sources, can be customised for different locations, and provides free access to sustainable materials. Future plans include expanding marketplace partnerships to enhance material reuse.

Build Reuse is a US-based online marketplace specialising in salvaged and surplus building materials. It connects buyers and sellers for reclaimed items like wood, bricks, fixtures, and architectural elements, promoting resource efficiency and reducing construction waste.

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Time for a Grown-Up Conversation on AI: The Future Demands It

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If you have seen me present recently – or even spoken to me for more than a few minutes, you’ve probably heard me go on about how the AI discussions need to change!  At the moment, most senior executives, board rooms, governments, think tanks and tech evangelists are running around screaming with their hands on their ears when it comes to the impact of AI on jobs and society.

We are constantly being bombarded with the message that AI will help make knowledge workers more productive.  AI won’t take people’s jobs – in fact it will help to create new jobs – you get the drift; you’ve been part of these conversations!

I was at an event recently where a leading cloud provider had a huge slide with the words: “Humans + AI Together” in large font across the screen. They then went on to demonstrate an opportunity for AI. In a live demo, they had the customer of a retailer call a store to check for stock of a dress. The call was handled by an AI solution, which engaged in a natural conversation with the customer. It verified their identity, checked dress stock at the store, processed the order, and even confirmed the customer’s intent to use their stored credit card.

So, in effect, on one slide, the tech provider emphasised that AI was not going to take our jobs, and two minutes later they showed how current AI capabilities could replace humans – today!

At an analyst event last week, representatives from three different tech providers told analysts how Microsoft Copilot is freeing up 10-15 hours a week. For a 40-hour work week, that’s a 25-38 time saving. In France (where the work week is 35 hours), that’s up to 43% of their time saved. So, by using a single AI platform, we can save 25-43% of our time – giving us the ability to work on other things.

What are the Real Benefits of AI?

The critical question is: What will we do with this saved time? Will it improve revenue or profit for businesses? AI might make us more agile, faster, more innovative but unless that translates to benefits on the bottom line, it is pointless. For example, adopting AI might mean we can create three times as many products. However, if we don’t make any more revenue and/or profit by having three times as many products, then any productivity benefit is worthless. UNLESS it is delivered through decreased costs.

We won’t need as many humans in our contact centres if AI is taking calls. Ideally, AI will lead to more personalised customer experiences – which will drive less calls to the contact centre in the first place! Even sales-related calls may disappear as personal AI bots will find deals and automatically sign us up. Of course, AI also costs money, particularly in terms of computing power. Some of the productivity uplift will be offset by the extra cost of the AI tools and platforms.

Many benefits that AI delivers will become table stakes. For example, if your competitor is updating their product four times a year and you are updating it annually, you might lose market share – so the benefits of AI might be just “keeping up with the competition”. But there are many areas where additional activity won’t deliver benefits. Organisations are unlikely to benefit from three times more promotional SMSs or EDMs and design work or brand redesigns.

I also believe that AI will create new roles. But you know what? AI will eventually do those jobs too. When automation came to agriculture, workers moved to factories. When automation came to factories, workers moved to offices. The (literally) trillion-dollar question is where workers go when automation comes to the office.

The Wider Impact of AI

The issue is that very few senior people in businesses or governments are planning for a future where maybe 30% of jobs done by knowledge workers go to AI. This could lead to the failure of economies. Government income will fall off a cliff. It will be unemployment on levels not seen since the great depression – or worse. And if we have not acknowledged these possible outcomes, how can we plan for it?

This is what I call the “grown up conversation about AI”. This is acknowledging the opportunity for AI and its impacts on companies, industries, governments and societies. Once we acknowledge these likely outcomes we can plan for it.

And that’s what I’ll discuss shortly – look out for my next Ecosystm Insight: The Three Possible Solutions for AI-driven Mass Unemployment.

AI Research and Reports
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Beyond Numbers: How Data Analysis Paves the Way for AI Careers

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Data analysts play a vital role in today’s data-driven world, providing crucial insights that benefit decision-making processes. For those with a knack for numbers and a passion for uncovering patterns, a career as a data analyst can be both fulfilling and lucrative – it can also be a stepping stone towards other careers in data. While a data analyst focuses on data preparation and visualisation, an AI engineer specialises in creating AI solutions, a machine learning (ML) engineer concentrates on implementing ML models, and a data scientist combines elements of data analysis and ML to derive insights and predictions from data.

Tools, Skills, and Techniques of a Data Analyst

Excel Mastery. Unlocks a powerful toolbox for data manipulation and analysis. Essential skills include using a vast array of functions for calculations and data transformation. Pivot tables become your secret weapon for summarising and analysing large datasets, while charts and graphs bring your findings to life with visual clarity. Data validation ensures accuracy, and the Analysis ToolPak and Solver provide advanced functionalities for statistical analysis and complex problem-solving. Mastering Excel empowers you to transform raw data into actionable insights.

Advanced SQL. While basic skills handle simple queries, advanced users can go deeper with sorting, aggregation, and the art of JOINs to combine data from multiple tables. Common Table Expressions (CTEs) and subqueries become your allies for crafting complex queries, while aggregate functions summarise vast amounts of data.  Window functions add another layer of power, allowing calculations within query results.  Mastering Advanced SQL empowers you to extract hidden insights and manage data with unparalleled precision.

Data Visualisation. Crafts impactful data stories. These tools empower you to connect to various data sources, transform raw information into a usable format, and design interactive dashboards and reports. Filters and drilldowns allow users to explore your data from different angles, while calculated fields unlock deeper analysis. Parameters add a final touch of flexibility, letting viewers customise the report to their specific needs. With tools Tableau and Power BI, complex data becomes clear and engaging.

Essential Python. This powerful language excels at data analysis and automation. Libraries like NumPy and Pandas become your foundation for data manipulation and wrangling. Scikit-learn empowers you to build ML models, while SciPy and StatsModels provide a toolkit for in-depth statistical analysis.  Python’s ability to interact with APIs and web scrape data expands its reach, and its automation capabilities streamline repetitive tasks. With Essential Python, you have the power to solve complex problems.

Automating the Journey. Data analysts can be masters of efficiency, and their skills translate beautifully into AI. Scripting languages like Ansible and Terraform automate repetitive tasks. Imagine streamlining the process of training and deploying AI models – a skill that directly benefits the AI development pipeline. This proficiency in automation showcases the valuable foundation data analysts provide for building and maintaining AI systems.

Developing ML Expertise. Transitioning from data analysis to AI involves building on your existing skills to develop ML expertise. As a data analyst, you may start with basic predictive models. This knowledge is expanded in AI to include deep learning and advanced ML algorithms. Also, skills in statistical analysis and visualisation help in evaluating the performance of AI models.

Growing Your AI Skills  

Becoming an AI engineer requires building on a data analysis foundation to focus on advanced skills such as:

  • Deep Learning. Learning frameworks like TensorFlow and PyTorch to build and train neural networks.
  • Natural Language Processing (NLP). Techniques for processing and analysing large amounts of natural language data.
  • AI Ethics and Fairness. Understanding the ethical implications of AI and ensuring models are fair and unbiased.
  • Big Data Technologies. Using tools like Hadoop and Spark for handling large-scale data is essential for AI applications.

The Evolution of a Data Analyst: Career Opportunities

Data analysis is a springboard to AI engineering. Businesses crave talent that bridges the data-AI gap.  Your data analyst skills provide the foundation (understanding data sources and transformations) to excel in AI. As you master ML, you can progress to roles like:

  • AI Engineer. Works on integrating AI solutions into products and services. They work with AI frameworks like TensorFlow and PyTorch, ensuring that AI models are incorporated into products and services in a fair and unbiased manner.
  • ML Engineer. Focuses on designing and implementing ML models. They focus on preprocessing data, evaluating model performance, and collaborating with data scientists and engineers to bring models into production. They need strong programming skills and experience with big data tools and ML algorithms.
  • Data Scientist. Bridges the gap between data analysis and AI, often involved in both data preparation and model development. They perform exploratory data analysis, develop predictive models, and collaborate with cross-functional teams to solve complex business problems. Their role requires a comprehensive understanding of both data analysis and ML, as well as strong programming and data visualisation skills.

Conclusion

Hone your data expertise and unlock a future in AI! Mastering in-demand skills like Excel, SQL, Python, and data visualisation tools will equip you to excel as a data analyst. Your data wrangling skills will be invaluable as you explore ML and advanced algorithms. Also, your existing BI knowledge translates seamlessly into building and evaluating AI models. Remember, the data landscape is constantly evolving, so continue to learn to stay at the forefront of this dynamic field. By combining your data skills with a passion for AI, you’ll be well-positioned to tackle complex challenges and shape the future of AI.

The Future of AI
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Harnessing Quantum Potential: Government and Technology Investments for Tomorrow

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Quantum computing is emerging as a groundbreaking force with the potential to reshape industries and enhance national security with unparalleled speed and precision. Governments and technology providers worldwide are heavily investing in this transformative technology, which promises significant advancements in areas such as cryptography, drug development, AI, and finance. Countries like Australia, Singapore, Taiwan, Qatar, and the UK are investing heavily in quantum research, backed by tech giants like Nvidia, IBM, and Google.

Ecosystm research finds that nearly 30% of enterprises are expecting to use quantum computing in the next 5 years.

Beyond Bits: Exploring the Potential of Quantum Computers

We need quantum computers because they have the potential to solve certain problems that are impossible (or impractical) for classical computers. Last year, Google led a study revealing that its quantum processor can complete a task in 6.18 seconds that would take a traditional supercomputer 47 years.

Here are a few reasons why quantum computing is exciting:

Unleashing the power of qubits. While classical computers use bits that can be either 0 or 1, quantum computers use qubits, which can exist in both states simultaneously (a state called superposition). This allows them to explore multiple possibilities simultaneously, making them significantly faster for specific tasks.

Tackling complex problems. Problems like simulating molecules or breaking complex encryption codes involve massive calculations. Quantum computers, with their unique properties, can manage these complexities more efficiently.

Revolutionising specific fields. Quantum computing has the potential to transform areas such as materials science, drug discovery, AI, and financial modelling. By simulating complex systems and processes, they could lead to breakthroughs in various sectors.

Quantum computers will not replace traditional computers entirely, but rather function as powerful tools for specific tasks beyond the reach of classical machines. Let’s look at cybersecurity as an example.

Twenty years ago, hacking was a basic task. Imagine a time before social media, when a simple computer and basic technical know-how were enough to breach a network. The stakes were low, the landscape uncomplicated. But technology, like threats, has evolved. Today’s hackers use sophisticated techniques, employing strategies like “harvest now, decrypt later” – stealing data today to decrypt later using more powerful machines. This is where quantum computing enters the scene, posing a significant threat to current encryption methods. In response, tech giants like Google, Apple, and Zoom are implementing quantum-resistant encryption into their software, safeguarding user data from potential future decryption attempts. Governments and telecommunication providers worldwide are boosting quantum encryption to tackle the potential security crisis.

The thrill of quantum computing lies in its infancy. Unforeseen applications, beyond our current imagination, could be unlocked as the technology matures.

Current Quantum Projects Focused on Security

First Scalable Network Secures Maritime Trade. The Netherlands is improving the resiliency of transport infrastructure in their own major international maritime hub, using quantum. The Port of Rotterdam Authority joined a collection of quantum technology firms to create a comprehensive cybersecurity ecosystem – the first of its kind globally. The port uses quantum technology to safeguard sensitive information, improving safety for the seagoing vessels carrying 470 million tonnes of cargo annually.

UK Integrates Quantum Navigation for Secure Air Travel. The UK is improving its digital transport infrastructure by integrating the first ever un-jammable aviation navigation system, powered by quantum software. This initiative was prompted by an incident where a government plane carrying the UK defence secretary had its GPS signal jammed close to Russian territory. This technology ensures safe and reliable navigation for aircraft, particularly in hostile environments. The UK government is investing USD 56 million into their quantum sector, aiming to become a quantum-enabled economy by 2033.

Governments Putting Faith in Quantum

Taiwan’s First Domestic 5-Qubit Computer. Taiwan is aiming to be a leader in quantum computing by building its first domestic machine by 2027. This initiative is part of a larger USD 259 million, five-year plan for quantum technology, and has a multi-pronged approach including building the actual quantum computer hardware; developing solutions to secure data in a world with quantum computers (quantum cryptography); creating a strong supply chain for quantum computing components within Taiwan; and collaborating with international partners to develop testing platforms and expertise.

Singapore Explores Real-World Applications. The Singaporean government has pledged USD 518 million to their National Quantum Strategy (NQS). This investment will provide the necessary resources to explore real-time applications of quantum technology in healthcare and technology. Simultaneously, they launched the National Quantum Processor Initiative (NQPI) to develop quantum sensors that will aid in research. Singapore aims to lead the world in quantum tech for investment portfolios, cryptography, and drug discovery.

Australia Aiming for World’s First Utility-Scale Machine. Backed by a USD 620 million investment from the Australian and Queensland governments, PsiQuantum aims to build a fault-tolerant computer that can solve previously challenging problems in fields like renewable energy, healthcare, and transportation. PsiQuantum’s innovative “fusion-based architecture” tackles scaling challenges by using millions of light-based qubits, paving the way for a new era of computational power and potentially sparking the next industrial revolution. This project positions Australia as a global leader in harnessing the immense potential of quantum computing.

Tech Companies Making the Quantum Leap

IBM Enhances Quantum Performance. IBM’s latest quantum computing platform, Qiskit 1.0, has worked on features that enhance performance, stability, and reliability. The updated open-source SDK aims to facilitate accessible quantum programming and accelerate processing times. Qiskit 1.0 uses optimised circuits to create and manage the interplay between classical and quantum computing. IBM is even collaborating with Japan’s AIST to develop a 10,000-qubit quantum computer by 2029, which is 75 times more powerful than current systems.

Microsoft and Quantinuum Achieve Reliable Logical Qubits. This significant milestone is said to mark a new era of dependable quantum technology, dramatically reducing errors and enhancing the precision of quantum computations. They have demonstrated an 800x improvement in error rates, paving the way for hybrid supercomputing systems that combine AI, high-performance computing (HPCs), and quantum capabilities to tackle scientific problems, with new capabilities becoming available to Azure Quantum Elements customers in the coming months.

Quantum Cloud Services for Enterprise. Major tech players QMware, Nvidia, and Oracle are teaming up to create hybrid quantum computing service for businesses. Combining classical and quantum computing, the project aims to crunch complex problems in AI, machine learning, and optimisation – all in the cloud.

Building Towards a Quantum Future

In the short term, using HPCs with quantum algorithms can already provide noticeable speed improvements over traditional methods. Hybrid approaches, where HPCs and quantum computers work together, could lead to significant gains in speed and efficiency, potentially ranging from 10x to 100x improvement.

Three strategies: quantum-inspired, hybrid, and full-scale quantum computing each offer distinct advantages.

While quantum-inspired computing leverages quantum algorithms to run on classical systems, hybrid computing combines classical and quantum processors, optimising the strengths of both to take complex problems more efficiently. Intuitively, full-scale quantum computing represents the ultimate goal, where large, fault-tolerant quantum computers solve problems beyond the reach of current classical systems.

Looking further ahead, the development of large-scale quantum computers could revolutionise industries by solving problems far beyond the reach of classical computers, with potential speedups of 500x to 1000x.

As quantum technology progresses, different industries and applications will benefit from tailored approaches that best suit their unique needs.

The Future of Industries
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Innovation in Government: Social, Economic, and Environmental Wins

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Governments worldwide struggle with intricate social, economic, and environmental challenges. Tight budgets often leave them with limited resources to address these issues head-on. However, innovation offers a powerful path forward.

By embracing new technologies, adapting to cultural shifts, and fostering new skills, structures, and communication methods, governments can find solutions within existing constraints.

Find out how public sector innovation is optimising internal operations, improving service accessibility, bridging the financial gap, transforming healthcare, and building a sustainable future.

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Click here to download ‘Innovation in Government: Social, Economic, and Environmental Wins’ as a PDF

Optimising Operations: Tech-Driven Efficiency

Technology is transforming how governments operate, boosting efficiency and allowing employees to focus on core functions.

Here are some real-world examples.

Singapore Streamlines Public Buses. A cloud-based fleet management system by the Land Transport Authority (LTA) improves efficiency, real-time tracking, data analysis, and the transition to electric buses.

Dubai Optimises Utilities Through AI. The Dubai Electricity and Water Authority (DEWA) leverages AI for predictive maintenance, demand forecasting, and grid management. This enhances service reliability, operational efficiency, and resource allocation for power and water utilities.

Automation Boosts Hospital Efficiency. Singapore hospitals are using automation to save man-hours and boost efficiency. Tan Tock Seng Hospital automates bacteria sample processing, increasing productivity without extra staff, while Singapore General Hospital tracks surgical instruments digitally, saving thousands of man-hours.

Tech for Citizens

Digital tools and emerging technologies hold immense potential to improve service accessibility and delivery for citizens. Here’s how governments are leveraging tech to benefit their communities.

Faster Cross-Border Travel. Malaysia’s pilot QR code clearance system expedites travel for factory workers commuting to Singapore, reducing congestion at checkpoints.

Metaverse City Planning. South Korea’s “Metaverse 120 Center” allows residents to interact with virtual officials and access services in a digital environment, fostering innovative urban planning and infrastructure management.

Streamlined Benefits. UK’s HM Revenue and Customs (HMRC) launched an online child benefit claim system that reduces processing time from weeks to days, showcasing the efficiency gains possible through digital government services.

Bridging the Financial Gap

Nearly 1.7 billion adults or one-third globally, remain unbanked.

However, innovative programs are bridging this gap and promoting financial inclusion.

Thailand’s Digital Wallet. Aimed at stimulating the economy and empowering underserved citizens, Thailand disburses USD 275 via digital wallets to 50 million low-income adults, fostering financial participation.

Ghana’s Digital Success Story. The first African nation to achieve 100% financial inclusion through modernised platforms like Ghana.gov and GhanaPay, which facilitate payments and fee collection through various digital channels.

Philippines Embraces QR Payments. The City of Alaminos leverages the Paleng-QR Ph Plus program to promote QR code-based payments, aligning with the central bank’s goal of onboarding 70% of Filipinos into the formal financial system by 2024.

Building a Sustainable Future

Governments around the world are increasingly turning to technology to address environmental challenges and preserve natural capital.

Here are some inspiring examples.

World’s Largest Carbon Capture Plant. Singapore and UCLA joined forces to build Equatic-1, a groundbreaking facility that removes CO2 from the ocean and creates carbon-negative hydrogen.

Tech-Enhanced Disaster Preparedness. The UK’s Lincolnshire County Council uses cutting-edge geospatial technology like drones and digital twins. This empowers the Lincolnshire Resilience Forum with real-time data and insights to effectively manage risks like floods and power outages across their vast region.

Smart Cities for Sustainability. Bologna, Italy leverages the digital twins of its city to optimise urban mobility and combat climate change. By analysing sensor data and incorporating social factors, the city is strategically developing infrastructure for cyclists and trams.

Tech for a Healthier Tomorrow

Technology is transforming healthcare delivery, promoting improved health and fitness monitoring.

Here’s a glimpse into how innovation is impacting patient care worldwide.

Robotic Companions for Seniors. South Korea tackles elder care challenges with robots. Companion robots and safety devices provide companionship and support for seniors living alone.

VR Therapy for Mental Wellness. The UAE’s Emirates Health Services Corporation implements a Virtual Reality Lab for Mental Health, that creates interactive therapy sessions for individuals with various psychological challenges. VR allows for personalised treatment plans based on data collected during sessions.

The Future of Industries
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Smart Solutions for Real Problems: Exploring Innovations in Southeast Asia’s Cities

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With over 70% of the world’s population predicted to live in cities by 2050, smart cities that use data, technology, and AI to streamline services are key to ensuring a healthy and safe environment for all who live, work, or visit them.

Fueled by rapid urbanisation, Southeast Asia is experiencing a smart city boom with an estimated 100 million people expected to move from rural areas to cities by 2030.

Despite their diverse populations and varying economic stages, ASEAN member countries are increasingly on the same page: they are all united by the belief that smart cities offer a solution to the complex urban and socio-economic challenges they face.

Read on to discover how Southeast Asian countries are using new tools to manage growth and deliver a better quality of life to hundreds of millions of people.

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Click here to download ‘Smart Solutions for Real Problems: Exploring Innovations in Southeast Asia’s Cities’ as a PDF

ASCN: A Network for Smarter Cities

The ASEAN Smart Cities Network (ASCN) is a collaborative platform where cities in the region exchange insights on adopting smart technology, finding solutions, and involving industry and global partners. They work towards the shared objective of fostering sustainable urban development and enhancing livability in their cities.

As of 2024, the ASCN includes 30 members, with new additions from Thailand and Indonesia.

“The ASEAN Smart Cities Network provides the sort of open platform needed to drive the smart city agenda. Different cities are at different levels of developments and “smartness” and ASEAN’s diversity is well suited for such a network that allows for cities to learn from one another.”

Taimur Khilji
UNITED NATIONS DEVELOPMENT PROGRAMME (UNDP)

Singapore’s Tech-Driven Future

The Smart Nation Initiative harnesses technology and data to improve citizens’ lives, boost economic competitiveness, and tackle urban challenges.

Smart mobility solutions, including sensor networks, real-time traffic management, and integrated public transportation with smart cards and mobile apps, have reduced congestion and travel times.

Ranked 5th globally and Asia’s smartest city, Singapore is developing a national digital twin to for better urban management. The 3D maps and subsurface model, created by the Singapore Land Authority, will help in managing infrastructure and assets.

The Smart City Initiative promotes sustainability with innovative systems like automated pneumatic waste collection and investments in water management and energy-efficient solutions.

Malaysia’s Holistic Smart City Approach

With aspirations to become a Smart Nation by 2040 (outlined in their Fourth National Physical Plan – NPP4), Malaysia is making strides.

Five pilot cities, including Kuala Lumpur and Johor Bahru, are testing the waters by integrating advanced technologies to modernise infrastructure.

Pilots embrace sustainability, with projects like Gamuda Cove showcasing smart technologies for intelligent traffic management and centralised security within eco-friendly developments.

Malaysia’s Smart Cities go beyond infrastructure, adopting international standards like the WELL Building Standard to enhance resident health, well-being, and productivity. The Ministry of Housing and Local Government, collaborating with PLANMalaysia and the Department of Standards Malaysia, has established clear indicators for Smart City development.

Indonesia’s Green Smart City Ambitions

Eyeing carbon neutrality by 2060, Indonesia is pushing its Smart City initiatives.

Their National Long-Term Development Plan prioritises economic growth and improved quality of life through digital infrastructure and innovative public services.

The goal is 100 smart cities that integrate green technology and sustainable infrastructure, reflecting their climate commitment.

Leaving behind congested Jakarta, Indonesia is building Nusantara, the world’s first “smart forest city“. Spanning 250,000 hectares, Nusantara will boast high-capacity infrastructure, high-speed internet, and cutting-edge technology to support the archipelago’s activities.

Thailand’s Smart City Boom

Thailand’s national agenda goes big on smart cities.

They aim for 105 smart cities by 2027, with a focus on transportation, environment, and safety.

Key projects include:

  • USD 37 billion smart city in Huai Yai with business centres and housing for 350,000.
  • A 5G-powered smart city in Ban Chang for enhanced environmental and traffic management.
  • USD $40 billion investment to create a smart regional financial centre across Chonburi, Rayong, and Chachoengsao.

Philippines Fights Urban Challenges with Smart Solutions

By 2050, population in cities is expected to soar to nearly 102 million – twice the current figure.

A glimmer of optimism emerges with the rise of smart city solutions championed by local governments (LGUs).

Rapid urbanisation burdens the Philippines with escalating waste. By 2025, daily waste production could reach a staggering 28,000 tonnes. Smart waste management solutions are being implemented to optimise collection and reduce fuel consumption.

Smart city developer Iveda is injecting innovation. Their ambitious USD 5 million project brings AI-powered technology to cities like Cebu, Bacolod, Iloilo, and Davao. The focus: leverage technology to modernise airports, roads, and sidewalks, paving the way for a more sustainable and efficient urban future.

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Coding-Evolved-How-AI-Tools-Boost-Efficiency-and-Quality
Coding Evolved: How AI Tools Boost Efficiency and Quality

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AI tools have become a game-changer for the technology industry, enhancing developer productivity and software quality. Leveraging advanced machine learning models and natural language processing, these tools offer a wide range of capabilities, from code completion to generating entire blocks of code, significantly reducing the cognitive load on developers. AI-powered tools not only accelerate the coding process but also ensure higher code quality and consistency, aligning seamlessly with modern development practices. Organisations are reaping the benefits of these tools, which have transformed the software development lifecycle. 

Ecosystm research indicates that close to half (nearly 50%) of Asia Pacific organisations are already leveraging AI tools for code generation, with an additional 32% actively evaluating similar GenAI tools

Impact on Developer Productivity 

AI tools are becoming an indispensable part of software development owing to their: 

  • Speed and Efficiency. AI-powered tools provide real-time code suggestions, which dramatically reduces the time developers spend writing boilerplate code and debugging. For example, Tabnine can suggest complete blocks of code based on the comments or a partial code snippet, which accelerates the development process. 
  • Quality and Accuracy. By analysing vast datasets of code, AI tools can offer not only syntactically correct but also contextually appropriate code suggestions. This capability reduces bugs and improves the overall quality of the software. 
  • Learning and Collaboration. AI tools also serve as learning aids for developers by exposing them to new or better coding practices and patterns. Novice developers, in particular, can benefit from real-time feedback and examples, accelerating their professional growth. These tools can also help maintain consistency in coding standards across teams, fostering better collaboration. 

Advantages of Using AI Tools in Development 

  • Reduced Time to Market. Faster coding and debugging directly contribute to shorter development cycles, enabling organisations to launch products faster. This reduction in time to market is crucial in today’s competitive business environment where speed often translates to a significant market advantage. 
  • Cost Efficiency. While there is an upfront cost in integrating these AI tools, the overall return on investment (ROI) is enhanced through the reduced need for extensive manual code reviews, decreased dependency on large development teams, and lower maintenance costs due to improved code quality. 
  • Scalability and Adaptability. AI tools learn and adapt over time, becoming more efficient and aligned with specific team or project needs. This adaptability ensures that the tools remain effective as the complexity of projects increases or as new technologies emerge. 

Deployment Models 

The choice between SaaS and on-premises deployment models involves a trade-off between control, cost, and flexibility. Organisations need to consider their specific requirements, including the level of control desired over the infrastructure, sensitivity of the data, compliance needs, and available IT resources. A thorough assessment will guide the decision, ensuring that the deployment model chosen aligns with the organisation’s operational objectives and strategic goals. 

SAAS Vs. On-Premises: A guide to choosing the right deployment model

Technology teams must consider challenges such as the reliability of generated code, the potential for generating biased or insecure code, and the dependency on external APIs or services. Proper oversight, regular evaluations, and a balanced integration of AI tools with human oversight are recommended to mitigate these risks. 

A Roadmap for AI Integration 

The strategic integration of AI tools in software development offers a significant opportunity for companies to achieve a competitive edge. By starting with pilot projects, organisations can assess the impact and utility of AI within specific teams. Encouraging continuous training in AI advancements empowers developers to leverage these tools effectively.  Regular audits ensure that AI-generated code adheres to security standards and company policies, while feedback mechanisms facilitate the refinement of tool usage and address any emerging issues. 

Technology teams have the opportunity to not only boost operational efficiency but also cultivate a culture of innovation and continuous improvement in their software development practices. As AI technology matures, even more sophisticated tools are expected to emerge, further propelling developer capabilities and software development to new heights. 

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