Case study: Smart cities & connected infrastructure — a sector comparison with benchmark KPIs

By 2025, the Asia-Pacific smart city market has reached USD 237 billion, with projections indicating growth to USD 608 billion by 2030—a compound annual growth rate of 20.7% that outpaces every other global region. Yet behind these staggering investment figures lies a more nuanced reality: cities across the region demonstrate wildly divergent outcomes on key performance indicators, with top performers achieving 40-60% reductions in urban carbon emissions while laggards struggle to move the needle beyond single-digit improvements. This case study examines what separates successful smart city implementations from underperforming ones, providing benchmark KPIs that product and design teams can use to evaluate, implement, and measure connected infrastructure solutions across the Asia-Pacific context.

Why It Matters

The urgency of smart city development in Asia-Pacific cannot be overstated. The region houses 60% of the world's urban population—approximately 2.4 billion people—with an additional 1.2 billion urban residents expected by 2050. This demographic pressure collides with acute climate vulnerability: seven of the ten countries most affected by extreme weather events are in Asia-Pacific, according to the 2024 Global Climate Risk Index. Cities consume over 75% of global primary energy and produce 70% of energy-related CO2 emissions, making urban transformation central to any credible decarbonization pathway.

In 2024-2025, several macro trends have accelerated smart city investments across the region. China's 14th Five-Year Plan allocated CNY 1.2 trillion (approximately USD 170 billion) specifically for new infrastructure including smart city technologies. India's Smart Cities Mission, now in its extended implementation phase, has disbursed over INR 207,000 crore (USD 25 billion) across 100 cities. Singapore's Smart Nation initiative continues to pioneer integrated urban systems, while South Korea's Digital New Deal 2.0 dedicates KRW 49 trillion (USD 38 billion) to digital infrastructure through 2025.

What distinguishes the Asia-Pacific context is the unique convergence of rapid urbanization, manufacturing capability, and policy ambition. Unlike mature markets where smart city retrofits dominate, Asia-Pacific includes numerous greenfield developments—from China's Xiong'an New Area to Indonesia's planned Nusantara capital—where integrated smart systems can be designed from inception. This creates both opportunities for holistic implementation and risks of technology lock-in without proper standards governance.

The stakes extend beyond environmental outcomes. McKinsey's 2024 analysis estimates that effective smart city implementation can improve quality of life indicators by 10-30%, reduce commute times by 15-20%, and generate municipal cost savings of 10-15% through operational efficiencies. For product teams building solutions in this space, understanding benchmark performance levels is essential for competitive positioning and genuine impact creation.

Key Concepts

Smart Cities

A smart city integrates information and communication technologies (ICT) with Internet of Things (IoT) devices to manage urban assets, resources, and services efficiently. The defining characteristic is not technology deployment per se, but the creation of feedback loops where data collection enables real-time optimization and evidence-based planning. The International Telecommunication Union defines smart sustainable cities as those that leverage ICT "to improve quality of life, efficiency of urban operation and services, and competitiveness, while ensuring that it meets the needs of present and future generations with respect to economic, social, environmental as well as cultural aspects."

In practice, smart city implementations span multiple domains: intelligent transportation systems, smart grids and distributed energy resources, connected water and waste management, environmental monitoring networks, and integrated building management systems. The most sophisticated deployments achieve interoperability across these domains through common data platforms and standardized APIs.

Micromobility

Micromobility refers to lightweight vehicles operating at speeds typically below 25 km/h, including e-bikes, e-scooters, and shared bicycle systems. Within smart city frameworks, micromobility serves as both a transportation mode and a data source. GPS-enabled shared vehicles generate granular mobility data that informs infrastructure planning, while their low-carbon profile (typically <20g CO2e per passenger-kilometer compared to >150g for private vehicles) directly supports emissions reduction targets.

Asia-Pacific leads global micromobility adoption, with China alone hosting over 1,000 bike-sharing programs serving more than 300 million registered users. Benchmark KPIs for micromobility systems include fleet utilization rates (target: >4 rides per vehicle per day), modal shift percentages (good: >15% of trips under 5km), and integration indices measuring connections with mass transit (leading cities achieve >40% of micromobility trips as first/last mile connections).

Life Cycle Assessment (LCA)

Life Cycle Assessment provides a systematic methodology for evaluating environmental impacts across a product or system's entire lifespan—from raw material extraction through manufacturing, use, and end-of-life disposal. For smart city infrastructure, LCA is essential for avoiding burden-shifting, where apparent emissions reductions in operational phases mask substantial embodied carbon in manufacturing or disposal.

Critical LCA boundaries for smart city technologies include the embodied carbon of IoT sensors (typically 5-15 kg CO2e per device), data center energy consumption (ranging from 0.4-0.8 PUE for best-in-class facilities versus >2.0 for inefficient operations), and network infrastructure emissions (approximately 0.5-1.0 kg CO2e per GB of data transmitted, depending on grid carbon intensity). Product teams should demand LCA-based comparisons rather than operational-only metrics when evaluating technology options.

Port Infrastructure

Smart port infrastructure represents a critical subsector within Asia-Pacific connected infrastructure, given the region's dominance in global shipping—nine of the world's ten busiest container ports are located in Asia-Pacific. Smart ports deploy automated guided vehicles, AI-optimized container stacking, shore power connections for vessels at berth, and integrated logistics platforms connecting maritime, rail, and road transport modes.

Key performance indicators for smart ports include berth productivity (leading ports achieve >150 moves per crane per hour), vessel turnaround time (benchmark: <24 hours for container vessels), and emissions intensity (best performers report <20 kg CO2 per TEU handled, compared to industry averages of 35-45 kg). The Port of Shanghai and Port of Singapore consistently rank among global leaders on these metrics.

Building Codes

Smart building codes establish mandatory or incentivized standards for building energy performance, connectivity requirements, and sustainability features. In the smart city context, codes increasingly require building automation systems, EV charging infrastructure provisions, and grid-interactive capabilities. Singapore's Green Mark scheme, updated in 2024, now mandates smart-ready certifications for new commercial buildings, requiring digital connectivity infrastructure and demand-response capability.

Benchmark metrics for smart buildings include energy use intensity (EUI) targets—leading Asia-Pacific commercial buildings achieve <100 kWh/m²/year compared to conventional buildings at 200-300 kWh/m²/year—and grid flexibility indices measuring the percentage of load that can respond to demand signals (advanced buildings demonstrate >30% flexible load capacity).

What's Working and What Isn't

What's Working

Integrated Command Centers with Cross-Domain Data Fusion

Cities that have invested in centralized operations centers integrating data from multiple urban systems demonstrate measurably superior outcomes. Hangzhou's City Brain platform, processing over 120 million data points daily from traffic cameras, transit systems, and emergency services, has reduced average commute times by 15.3% and emergency response times by 48%. The success factor is not merely data aggregation but the development of AI models that identify cross-system optimization opportunities—for example, adjusting traffic signals in real-time based on bus locations to improve transit reliability while managing overall network flow.

Seoul's Integrated Operations Center (SIOC) similarly demonstrates the value of cross-domain integration, connecting 282 separate information systems across transportation, disaster response, and environmental monitoring. The center's coordinated response capabilities have reduced urban flooding damage by 35% through predictive drainage management triggered by weather monitoring data. The benchmark for effective integration appears to be connecting at least five distinct urban systems through a common data platform with sub-minute latency.

District-Scale Energy Management with Storage Integration

Smart city districts achieving the deepest decarbonization combine renewable generation, battery storage, and intelligent load management at neighborhood scale. Japan's Fujisawa Sustainable Smart Town, developed by Panasonic, demonstrates district-level energy independence of 70%, with residential solar generation, community battery storage (1.5 MWh capacity), and automated demand response reducing per-capita emissions by 70% compared to national averages.

Similar outcomes appear in Singapore's Tengah "Forest Town," where district cooling systems achieve coefficient of performance (COP) values exceeding 5.5 (compared to conventional AC systems at 2.5-3.5), and building-integrated photovoltaics generate approximately 2.3 MWh per housing unit annually. The critical success factor is designing energy systems at district rather than building scale, enabling load diversity benefits and shared storage economics that are unachievable in single-building implementations.

Mobility-as-a-Service (MaaS) Integration Achieving Modal Shift

Cities that have implemented comprehensive MaaS platforms—providing unified planning, booking, and payment across public transit, micromobility, and ride-hailing—demonstrate genuine behavioral change in transportation patterns. Taipei's integrated Easycard system and YouBike micromobility network have increased non-private-vehicle mode share to 58% for commute trips, among the highest in Asia-Pacific. The key metrics include payment integration (Taipei achieves >90% trips using unified fare media), real-time integration (<30 second refresh rates for multimodal routing), and first/last mile coverage (micromobility stations within 300 meters of 85% of metro exits).

What Isn't Working

Siloed Pilot Projects Without Pathway to Scale

The most common failure mode in Asia-Pacific smart city development is the proliferation of disconnected pilot projects that demonstrate technical feasibility but never achieve city-wide deployment or cross-sector integration. India's Smart Cities Mission has funded over 6,000 individual projects, but audits reveal that fewer than 15% have achieved intended scale, with many remaining as isolated technology demonstrations without interoperability or sustainability plans.

The root cause is typically procurement structures that favor point-solution vendors over systems integrators, combined with municipal capacity constraints that prevent technical staff from managing complex multi-vendor ecosystems. Product teams should benchmark against deployment scale—successful implementations typically require phased rollouts reaching at least 20% of target coverage within 24 months to demonstrate viability.

Underestimating Cybersecurity and Data Governance Requirements

Connected infrastructure creates attack surfaces that many Asia-Pacific municipalities have inadequately addressed. A 2024 survey by Frost & Sullivan found that 67% of smart city projects in ASEAN countries lacked comprehensive cybersecurity frameworks, with 38% having experienced at least one significant breach or disruption. The interconnection that enables smart city benefits also creates cascade failure risks—attacks on traffic management systems can propagate to emergency services and vice versa.

Data governance presents parallel challenges. Privacy regulations vary dramatically across Asia-Pacific—from comprehensive frameworks in Japan and South Korea to nascent rules in emerging markets—creating compliance complexity for solution providers. Benchmark implementations require security operations centers with 24/7 monitoring, penetration testing at minimum quarterly intervals, and documented data governance policies with citizen consent mechanisms.

Neglecting Social Inclusion and Digital Equity

Smart city implementations that optimize primarily for efficiency metrics often exacerbate existing inequalities. Sensor networks and digital services concentrate in affluent districts while underserving informal settlements. Elderly populations and low-income residents lacking smartphone access are excluded from app-based services. The UN-Habitat 2024 report on smart cities in Asia found that 73% of projects had no specific provisions for accessibility or digital inclusion.

Leading implementations address equity through explicit targeting—ensuring sensor coverage and service availability in underserved areas—and through multi-channel service delivery that doesn't require smartphone ownership. Benchmark metrics include geographic equity indices measuring service availability variance across income quintiles and accessibility compliance rates for digital platforms.

Key Players

Established Leaders

Huawei Technologies dominates the Asia-Pacific smart city platform market, with implementations across 200+ cities in 50+ countries. The company's Horizon Digital Platform provides integrated capabilities for smart lighting, traffic management, and IoT device management. Revenue from government and infrastructure segments exceeded USD 15 billion in 2024.

Siemens operates major smart city infrastructure across the region, including the integrated building management and grid systems at Singapore's Changi Airport Terminal 5 and the Desigo CC platform deployed across hundreds of commercial buildings in Greater China. The company's MindSphere IoT platform serves as the connectivity backbone for industrial and infrastructure applications.

Hitachi has evolved from hardware manufacturing to smart city solutions, with the Lumada IoT platform supporting urban mobility, energy management, and public safety applications across Japan and Southeast Asia. The company's acquisition of GlobalLogic strengthened its software integration capabilities for municipal clients.

Alibaba Cloud extends beyond cloud computing into smart city platforms through its ET City Brain technology, deployed across 30+ cities in China and exported to Malaysia and Thailand. The platform's strength lies in AI-driven optimization algorithms that continuously improve urban operations.

NEC Corporation provides biometric identification, public safety, and communication infrastructure across Asia-Pacific smart cities, with particular strength in disaster early warning systems deployed throughout Japan's earthquake and tsunami monitoring networks.

Emerging Startups

Aclima (Singapore/US) deploys hyperlocal air quality monitoring networks that generate block-level pollution data for urban planning decisions. The company's mobile sensing platform, mounted on public transit vehicles, creates environmental maps at 100x the resolution of traditional monitoring stations.

Swiftly (Singapore) provides transit analytics platforms that help public transport operators optimize schedules and improve reliability. The company's real-time vehicle tracking and passenger flow analytics serve transit agencies in Singapore, Australia, and Japan.

Tessera Solar (India) develops prefabricated solar microgrids for urban deployments, reducing installation costs by 40% compared to conventional rooftop systems. The company's building-integrated photovoltaic solutions are designed specifically for tropical climate optimization.

Urban.io (Australia) offers AI-powered building energy management platforms that have demonstrated 20-30% energy savings in commercial buildings across Sydney, Melbourne, and Singapore through automated HVAC optimization and predictive maintenance.

Gogoro (Taiwan) has built Asia's largest battery-swapping network for electric two-wheelers, with over 12,000 GoStations serving 600,000+ subscribers. The company's infrastructure-as-a-service model provides a template for electrified urban micromobility at scale.

Key Investors & Funders

Temasek Holdings has invested over SGD 8 billion in smart city technologies through direct investments and its subsidiary Surbana Jurong, which provides urban planning and engineering services across Asia-Pacific.

Asian Development Bank approved USD 3.2 billion in smart city and sustainable urban development financing in 2024, with major programs in Indonesia, the Philippines, and Vietnam focusing on integrated urban infrastructure.

SoftBank Vision Fund has backed numerous smart city-adjacent companies including mobility platforms, logistics automation, and IoT infrastructure, with Asia-Pacific investments exceeding USD 50 billion since inception.

GIC Private Limited has deployed substantial capital into sustainable infrastructure across Asia-Pacific, including smart building portfolios and renewable energy assets integrated with urban development projects.

JICA (Japan International Cooperation Agency) provides concessional financing for smart city projects across Southeast Asia, with particular focus on technology transfer from Japanese solution providers and capacity building for municipal technical staff.

Examples

1. Singapore's Punggol Digital District: Integrated Planning from Inception

Singapore's Punggol Digital District represents a 50-hectare greenfield smart district development designed as an integrated testbed for connected infrastructure. Developed by JTC Corporation with completion phases from 2023-2028, the district incorporates the Open Digital Platform (ODP)—a common data infrastructure enabling interoperability across building management, district cooling, autonomous transport, and environmental monitoring systems.

Specific Metrics:

• District cooling COP: 5.8 (42% more efficient than conventional systems)
• Building energy use intensity: 85 kWh/m²/year (50% below Singapore code requirements)
• Autonomous vehicle readiness: 100% of internal roads designed for SAE Level 4 operation
• Digital twin coverage: Real-time 3D modeling of all buildings, utilities, and transport systems
• Target carbon emissions: 40% below Singapore 2030 baseline

The key lesson from Punggol is the value of establishing common data architecture before physical construction, enabling buildings and infrastructure systems to be designed for interoperability rather than retrofitted afterward.

2. Hangzhou's City Brain: AI-Optimized Traffic Management at Scale

Hangzhou's City Brain, developed in partnership with Alibaba Cloud, processes data from 1,300 traffic signals, 4,500 traffic cameras, and municipal bus GPS systems to optimize city-wide traffic flow in real-time. The system has expanded from traffic management to include 48 government applications across urban services.

Specific Metrics:

• Average vehicle speed improvement: 15.3% on covered road network
• Emergency vehicle response time: Reduced from 15 minutes to 7 minutes average
• Traffic signal optimization: 128 intersections adjusted automatically per second
• Daily data processing: 120 million data points analyzed
• ROI timeline: Full capital cost recovery in 18 months through reduced congestion costs

Hangzhou demonstrates that AI optimization can deliver measurable improvements at metropolitan scale, though the implementation required substantial investment in sensing infrastructure and municipal data governance frameworks that took years to develop.

3. Seoul's Green Smart City Pilot: Retrofit Approach in Mature Urban Context

Unlike greenfield developments, Seoul's Magok district transformation demonstrates smart city implementation through retrofit of existing urban areas. The project integrates smart street lighting (8,500 connected luminaires), urban agriculture monitoring, waste collection optimization, and air quality networks across a 3.67 km² mixed-use district.

Specific Metrics:

• Street lighting energy reduction: 72% through adaptive dimming
• Waste collection efficiency: 35% reduction in collection vehicle-kilometers
• Air quality monitoring: 200 sensor nodes providing 50m grid resolution
• Urban heat island mitigation: 2.1°C reduction through green infrastructure and smart irrigation
• Citizen engagement: 89% smartphone app adoption for service feedback

Seoul's approach emphasizes incrementalism—deploying connected infrastructure progressively and demonstrating value at each phase to build political support for continued investment. This contrasts with the large upfront capital requirements of comprehensive greenfield implementations.

Action Checklist

• Conduct baseline assessment of current city/district performance across energy, mobility, waste, and environmental KPIs before initiating smart city investments
• Establish common data platform architecture and API standards before procuring point solutions to ensure future interoperability
• Require LCA-based environmental impact assessments for all smart infrastructure components, including embodied carbon and end-of-life considerations
• Develop cybersecurity framework with 24/7 monitoring, quarterly penetration testing, and incident response procedures before connecting critical infrastructure systems
• Create digital inclusion strategy ensuring service accessibility for elderly, low-income, and smartphone-free populations through multi-channel delivery
• Establish geographic equity metrics and monitoring to ensure smart city investments don't concentrate benefits in affluent areas
• Design phased deployment plans targeting minimum 20% coverage within 24 months to validate scalability before full investment commitment
• Implement cross-domain data governance policies with clear citizen consent mechanisms and data minimization principles
• Build municipal technical capacity through training programs and secondments before vendor relationships, reducing dependency on external support
• Create feedback loops connecting operational data to urban planning decisions, closing the gap between smart city monitoring and long-term infrastructure investment

FAQ

Q: What are the most important KPIs for measuring smart city success? A: The highest-impact KPIs vary by city context but generally fall into three categories. Efficiency metrics include energy use intensity (target: <100 kWh/m²/year for commercial buildings), water loss rates (target: <15% non-revenue water), and transit system reliability (>95% on-time performance). Sustainability metrics include per-capita CO2 emissions (leading cities achieve <4 tonnes/year), renewable energy share (>30% of grid supply), and waste diversion rates (>60%). Equity metrics include service availability variance across income quintiles (<20% difference between highest and lowest), digital platform accessibility compliance (>90% WCAG 2.1 compliance), and citizen satisfaction scores (target: >70% positive ratings). Most critically, KPIs should be selected based on materiality to local priorities—coastal cities may prioritize flood resilience metrics, while industrial cities emphasize air quality improvements.

Q: How much should a city budget for smart city infrastructure? A: Benchmarks vary substantially by implementation scope and development context. Retrofit projects typically require USD 50-150 per capita in initial capital investment, with annual operating costs of 10-15% of capital. Greenfield developments integrating smart infrastructure from design phase typically add 3-8% to total development costs but achieve superior performance outcomes. Cities should budget for 5-7 year implementation timelines with phased investment tranches tied to demonstrated outcomes. The most common budgeting error is underestimating ongoing data platform and cybersecurity operations costs, which often exceed initial projections by 40-60%.

Q: What governance structures support successful smart city implementation? A: Leading implementations typically establish dedicated smart city offices with cross-departmental authority, reporting directly to mayor or city manager level. Singapore's Smart Nation and Digital Government Group exemplifies this model with cabinet-level leadership. Technical governance requires data governance committees establishing standards for interoperability, privacy, and security across municipal departments. Citizen governance through digital advisory panels and participatory budgeting for smart city investments increases public trust and adoption. The most effective structures combine centralized platform management with decentralized application development, allowing individual departments to innovate on shared infrastructure.

Q: How do smart cities manage vendor lock-in risks? A: Vendor lock-in represents a significant risk given proprietary platforms from major providers. Mitigation strategies include requiring open APIs and data portability as contractual obligations, selecting solutions built on open standards (particularly important for IoT device protocols and data formats), maintaining ownership of all collected data in city-controlled repositories, and building internal technical capacity to manage integrations rather than depending entirely on vendor support. The EU's Minimal Interoperability Mechanisms (MIMs) provide a useful framework that Asia-Pacific cities are increasingly adopting for procurement specifications.

Q: What role does private sector partnership play in smart city financing? A: Private sector partnerships are essential given the capital intensity of smart city infrastructure. Effective models include build-operate-transfer arrangements for specific subsystems (particularly street lighting and EV charging infrastructure), outcome-based contracts linking payments to achieved KPIs, and data-sharing agreements where private platforms provide municipal insight in exchange for operating permissions. Singapore's collaboration with industry partners in Punggol Digital District demonstrates hybrid financing where government provides land and baseline infrastructure while private developers fund smart building systems with regulatory incentives. The key success factor is aligning incentive structures so that private partners benefit from achieving public outcomes rather than merely deploying technology.

Sources

• International Telecommunication Union (2024). "United for Smart Sustainable Cities: KPI Benchmarking Framework." Geneva: ITU Publications.
• McKinsey Global Institute (2024). "Smart Cities in Asia-Pacific: Technology Progress and Investment Outlook." McKinsey & Company.
• Asian Development Bank (2024). "Creating Livable Asian Cities: Smart City Development Progress Report." Manila: ADB Publications.
• UN-Habitat (2024). "Global Smart City Index: Asia-Pacific Regional Analysis." Nairobi: United Nations Human Settlements Programme.
• Frost & Sullivan (2024). "ASEAN Smart Cities Market Assessment and Cybersecurity Landscape." Singapore: Frost & Sullivan.
• World Economic Forum (2024). "Global Future Council on Cities and Urbanization: Connected Infrastructure Standards Report." Geneva: WEF Publications.
• Singapore Urban Redevelopment Authority (2025). "Punggol Digital District Development Framework and Performance Monitoring." Singapore: URA.
• Hangzhou Municipal Government (2024). "City Brain Implementation Report: Five Years of AI-Enabled Urban Operations." Hangzhou Smart City Office.