10 Ways Technology Is Revolutionizing Urban Infrastructure

Cities are the world’s engines of culture and commerce—and increasingly, the frontline of climate risk and population growth. With more than half of humanity already living in urban areas and the share projected to rise to roughly two-thirds by 2050, the stakes for reliable, equitable, and sustainable infrastructure could not be higher. Urban areas also account for a major share of global energy use and emissions, which means the systems we build and modernize now will shape environmental and economic outcomes for decades. This article breaks down ten high-impact ways technology is transforming urban infrastructure today—what each innovation is, how to get started, and how to measure real progress.

Key takeaways

• Target quick wins first. Start with pilot deployments in high-leverage corridors, districts, or facilities, then scale what works.
• Measure relentlessly. Define a handful of outcome metrics (travel time reliability, outage minutes, leak volume, EUI, fill-level overflows, etc.) before you deploy.
• Build on standards. Open data schemas, openBIM, and recognized city KPIs reduce vendor lock-in and integration headaches.
• Design for security and privacy. Treat cyber, data minimization, and governance as core requirements—not add-ons.
• Plan for people. Combine automation with training, change management, and plain-language public communication to turn tech into trust.

1) Intelligent Transportation Systems (ITS) and Real-Time Traffic Management

What it is & why it matters
ITS uses sensors, cameras, connected signals, transit priority, dynamic signage, and data platforms to manage traffic in real time. Done right, it improves travel time reliability, reduces delays and crashes, and makes buses faster and more predictable.

Requirements & low-cost alternatives

• Core: Signal controllers capable of adaptive timing, communications (fiber, cellular, or dedicated radio), detection (loops, radar, or video), a traffic management platform, and trained operators.
• Nice-to-have: Transit signal priority (TSP), curb/parking management, incident detection, and work-zone systems.
• Low-cost start: Retime signals on a data-driven schedule, deploy TSP on one bus corridor, use portable radar counters to gather baselines.

Step-by-step

1. Map corridors with the worst delays and crash hot spots; collect before-data (speeds, buffers, on-time transit).
2. Upgrade communications and controllers; calibrate detection.
3. Deploy adaptive timing and TSP on a pilot corridor; stand up a small control room function.
4. Publish traveler information (SMS, web, GTFS-realtime).
5. Expand by “rings” from the pilot if KPIs improve.

Beginner modifications & progressions

• Simplify: Fixed-time retiming with weekend plans.
• Scale up: Citywide adaptive control, integrated corridor management, freight signal priority.

Recommended metrics
Travel time index; buffer index; on-time arrival for buses; crash frequency and severity; queue spillback counts.

Safety, caveats, mistakes to avoid

• Over-fitting signal plans to one data season; ignoring crosswalk times and accessibility; deploying cameras without clear privacy policies; skipping interagency MOUs for incident response.

Mini-plan

• Week 1: Baseline counts and travel times on a 3–5 km corridor.
• Week 2: Retiming + transit priority at 10–12 intersections.
• Week 6: Review KPIs; decide to extend or adjust.

2) Smart Grids, Microgrids, and Demand Response

What it is & why it matters
A smart grid couples sensors, advanced metering, analytics, and automation to manage supply and demand. Microgrids keep critical sites (hospitals, data centers, shelters) running during main-grid outages and integrate local solar and storage. Demand response shifts or trims loads during peaks.

Requirements & low-cost alternatives

• Core: AMI/advanced meters, distribution automation, DER interconnection rules, utility–city data-sharing agreements.
• Nice-to-have: Microgrids at critical facilities, building automation interfaces, bidirectional EV charging at depots.
• Low-cost start: Demand response for municipal buildings; thermal storage at one arena or campus.

Step-by-step

1. Identify critical facilities and peak demand drivers (pumping stations, arenas, chilled water).
2. Add submeters and building controls to create visible load profiles.
3. Enroll in a utility DR program; test manual curtailment events.
4. Add controls for automated curtailment (lighting/HVAC setpoints) and install battery storage where payback pencils out.
5. Plan a microgrid for one high-impact site (school shelter or hospital), including islanding tests.

Beginner modifications & progressions

• Simplify: “DR-lite” event playbooks and manual setpoint nudges.
• Scale up: Multiple microgrids, aggregated city fleet V2G, distribution-level energy management systems.

Recommended metrics
SAIDI/SAIFI (outage duration/frequency), peak kW reduced, DR event performance, critical-facility uptime hours, DER interconnection time.

Safety, caveats, mistakes to avoid

• Underestimating interconnection timelines; ignoring cybersecurity for OT networks; overpromising V2G revenue before pilots prove reliability; skipping islanding drills.

Mini-plan

• Design: Select a community center for a solar-plus-storage microgrid.
• Implement: Install AMI and automate HVAC load shed at city hall.
• Prove: Run two DR events; report kW reduced and comfort impacts.

3) Digital Twins and City-Scale Simulation

What it is & why it matters
A digital twin is a living, data-connected 3D model of the city—assets, terrain, utilities, traffic, and buildings—used to test scenarios (new bus lanes, stormwater projects, heat mitigation, zoning) before spending capital. It turns spreadsheets into spatial decisions.

Requirements & low-cost alternatives

• Core: 3D basemap (LiDAR/photogrammetry), asset inventory, open APIs, analytics engine, governance for updates.
• Nice-to-have: Real-time feeds (signals, weather, flood sensors), co-simulation (energy, mobility, water).
• Low-cost start: Begin with one district and a handful of datasets (buildings, trees, traffic counts).

Step-by-step

1. Inventory authoritative data; define a single “source of truth.”
2. Stand up an open 3D base model; connect priority live feeds.
3. Run one decision use-case (e.g., site a cooling center network; compare bus-only lane options).
4. Publish a public viewer for transparency; log what changed because of the simulation.
5. Set update cadences; expand department by department.

Beginner modifications & progressions

• Simplify: Static 3D for permitting and communication.
• Scale up: Multi-utility interdependencies, flood/heat co-simulation, automated permit checks from models.

Recommended metrics
Time saved in analysis cycles, number of decisions influenced, modeling accuracy vs. observed outcomes, and reuse of shared datasets.

Safety, caveats, mistakes to avoid

• Treating the twin as a one-time “3D photo”; poor metadata; failure to version models; insufficient privacy controls for sensor overlays.

Mini-plan

• Pilot: Create a 3D model for a regeneration district.
• Use: Test three street designs and publish resulting safety/throughput changes.
• Scale: Add stormwater layers for the same area next quarter.

4) Smart Water and Wastewater Networks

What it is & why it matters
Smart meters, pressure/flow sensors, acoustic leak detection, and predictive maintenance cut losses, reduce energy, and protect public health. In sewers and stormwater, sensors and gates can prevent overflows and flooding.

Requirements & low-cost alternatives

• Core: District metered areas (DMAs), AMI water meters, SCADA integration, GIS-linked asset registry, leak detection tools.
• Nice-to-have: Smart valves, smart stormwater controls, performance-based NRW contracts.
• Low-cost start: Create two DMAs with night-flow monitoring; deploy a temporary acoustic survey.

Step-by-step

1. Establish a water balance and baseline non-revenue water (NRW).
2. Stand up DMAs and pressure monitors; log night-flow anomalies.
3. Pair leak surveys with targeted pressure management; replace under-registering meters.
4. In wastewater, add level sensors at overflow points and optimize pump schedules.
5. Institutionalize annual audits and five-year NRW plans.

Beginner modifications & progressions

• Simplify: Manual leak surveys + meter testing where budgets are tight.
• Scale up: Contracted, outcome-based NRW reduction; citywide AMI with customer portals.

Recommended metrics
NRW by volume, leaks found and fixed per km, energy per m³ pumped, overflows prevented, customer outage minutes.

Safety, caveats, mistakes to avoid

• Using only NRW % instead of absolute volumes; skipping calibration; failing to align tariff and conservation messaging; insufficient valve maintenance.

Mini-plan

• DMA start: Instrument a 5–10 km² zone; track night flow for 30 days.
• Action: Prioritize top leaks and pressure steps; verify savings after repairs.

5) High-Performance Buildings and Automation

What it is & why it matters
Building automation systems (BAS), advanced controls, submetering, and benchmarking reduce energy, improve comfort, and make buildings flexible grid assets. Portfolio-wide benchmarking identifies best and worst performers so you invest where it matters.

Requirements & low-cost alternatives

• Core: Benchmarking platform, interval meters, open-protocol BAS, retro-commissioning playbooks.
• Nice-to-have: Fault detection and diagnostics (FDD), occupancy analytics, automated demand response.
• Low-cost start: Start with benchmarking and “tune-ups” (scheduling, economizers, setbacks).

Step-by-step

1. Benchmark all municipal buildings; set Energy Use Intensity (EUI) targets.
2. Install submeters at high-consumption sites; fix low-cost control issues.
3. Add FDD and DR capabilities to the top 5 energy users.
4. Tie building controls into microgrid/DR events; measure comfort outcomes.
5. Require commissioning and open protocols in all new projects.

Beginner modifications & progressions

• Simplify: Night/weekend scheduling and temperature deadbands.
• Scale up: Portfolio-wide FDD with automated work orders; performance contracts.

Recommended metrics
EUI by building, peak kW shaved, DR event kW, avoided maintenance calls, occupant comfort scores.

Safety, caveats, mistakes to avoid

• Proprietary lock-in; over-tightening setpoints; ignoring ventilation and indoor air quality; inadequate cybersecurity for BAS networks.

Mini-plan

• Week 1–2: Benchmark and identify worst-quartile buildings.
• Week 3–6: Implement low-cost fixes; enroll in one DR program and test response.

6) Smart Waste and Circular Systems

What it is & why it matters
Fill-level sensors, route optimization, RFID tags, and pricing reforms (e.g., variable-rate “pay-as-you-throw”) reduce truck miles, litter, and landfill dependence while improving recycling and composting.

Requirements & low-cost alternatives

• Core: Container sensors on selected routes, routing software, materials tracking, outreach.
• Nice-to-have: Smart transfer stations with weight-in-motion, contamination detection, reverse-logistics pilots.
• Low-cost start: Instrument a subset of commercial bins and re-optimize pickups.

Step-by-step

1. Baseline diversion rate, missed pickups, overflow incidents, and route miles.
2. Install sensors on high-problem bins; build optimized routes.
3. Pilot variable-rate pricing with contamination enforcement tools.
4. Add organics collection where feasible; integrate outreach and small grants.
5. Publish results; iterate routes quarterly.

Beginner modifications & progressions

• Simplify: Manual overflow reporting via 311; static route refinements.
• Scale up: Citywide variable pricing and depot automation.

Recommended metrics
Overflow incidents per 100 bins, kg diverted per household, route miles per ton, contamination rate.

Safety, caveats, mistakes to avoid

• Deploying sensors everywhere at once; pricing changes without equity protections; ignoring multi-family building needs.

Mini-plan

• Pilot: 500 sensors across three neighborhoods.
• Evaluate: 90-day comparison of pickups/overflows vs. baseline; decide where to expand.

7) Urban Connectivity as a Utility (Fiber, 5G, and LPWAN)

What it is & why it matters
Fiber backbones power everything else: traffic signals, public safety networks, civic Wi-Fi, and private broadband. 5G adds low-latency mobility and network slicing for mission-critical services. Low-power wide-area networks (like LoRaWAN) connect thousands of sensors—air quality, parking, water—at very low energy and cost.

Requirements & low-cost alternatives

• Core: City fiber plan (including dig-once policies), neutral-host small-cell permitting, LPWAN gateways, and a device onboarding process.
• Nice-to-have: Municipal dark fiber leasing, city-owned IoT network, and coverage analytics.
• Low-cost start: Deploy a handful of LoRaWAN gateways for water/air sensors; map existing fiber and ducts.

Step-by-step

1. Inventory existing conduits and strands; publish a standard spec for attachments.
2. Prioritize civic corridors (signals, schools, libraries); coordinate trenching with utility works.
3. Stand up a basic LPWAN; certify two sensor types.
4. Pilot 5G use-cases (connected intersections, CCTV, emergency comms) with clear SLAs.
5. Expand coverage tied to capital projects; require open APIs for city devices.

Beginner modifications & progressions

• Simplify: Share fiber with anchor institutions first.
• Scale up: Neutral-host marketplaces, public–private broadband, private 5G on campuses.

Recommended metrics
Backbone uptime, fiber miles added per year, percentage of critical assets on redundant paths, IoT device onboarding times, coverage gaps closed.

Safety, caveats, mistakes to avoid

• Fragmented permitting; neglecting Equity (affordability) alongside availability; deploying sensors without lifecycle management; weak key management for IoT.

Mini-plan

• Start: Install three LPWAN gateways; connect storm sensors.
• Next: Target two fiber spurs to schools and a bus depot; publish open API endpoints.

8) Public Safety, Early Warning, and Urban Resilience Tech

What it is & why it matters
Multi-hazard early warning systems, environmental sensors, and resilient communications can significantly reduce disaster losses and protect vulnerable residents. Heat, floods, storms, and air quality extremes all benefit from timely alerts and pre-planned actions.

Requirements & low-cost alternatives

• Core: Hazard monitoring (weather, river levels, air quality), alerting channels (cell broadcast/SMS/sirens), playbooks, and community partner networks.
• Nice-to-have: Decision support that combines forecasts with exposure (buildings, populations), backup power for critical nodes.
• Low-cost start: SMS/IVR alerts for heat and flood zones; equip shelters with battery backups.

Step-by-step

1. Map at-risk groups and assets; define multilingual alert templates.
2. Connect to authoritative hazard feeds; test end-to-end alerts.
3. Run tabletop drills; measure signup and delivery rates.
4. Add sensors (stream gauges, flood cameras, AQ monitors) at known hot spots.
5. Formalize after-action reviews and publish improvements.

Beginner modifications & progressions

• Simplify: Use existing national alert channels first.
• Scale up: Citywide multi-hazard platform, community liaisons, and backup mesh communications.

Recommended metrics
Warning lead time, delivery rate, shelter activation time, outage hours avoided, recovery time.

Safety, caveats, mistakes to avoid

• Single-channel alerts; failure to reach non-digital residents; unclear authority for issuing warnings; no backup power at critical sites.

Mini-plan

• Deploy: Heat alerts to pre-registered residents + automated cooling center map.
• Verify: Measure opt-in, message delivery, and center occupancy during the first heat event.

9) Digital Permitting, Inspections, and Automated Code Checking

What it is & why it matters
Digitized permitting portals, electronic plan reviews, and automated code compliance checking reduce approval times and errors while increasing transparency. When aligned to openBIM standards, agencies can check models instead of deciphering 2D PDFs.

Requirements & low-cost alternatives

• Core: Online portal, plan review workflow, e-payments, role-based access, and clear service levels.
• Nice-to-have: openBIM submissions (IFC), automated rule checking for common code items, digital inspections with photo/video.
• Low-cost start: Move top five permit types online; standardize checklists and target timelines.

Step-by-step

1. Map current processes; remove redundant steps before digitizing.
2. Launch a portal with status tracking and a help desk.
3. Pilot IFC-based submission for simple use-cases (e.g., parking counts, accessibility clearances).
4. Introduce automated checks for a small ruleset; expand iteratively.
5. Publish monthly performance dashboards.

Beginner modifications & progressions

• Simplify: E-submittals with manual review.
• Scale up: Rule libraries, cross-agency reviews in one gateway, and analytics on delays.

Recommended metrics
Median days to decision, resubmittal rates, inspection pass/fail rates, customer satisfaction, and percentage of digital submissions.

Safety, caveats, mistakes to avoid

• Digitizing broken processes “as-is”; black-box automation without appeals; inaccessible portals; not aligning model submission standards early.

Mini-plan

• Phase 1: Put minor permits online with tracked SLAs.
• Phase 2: Pilot automated checks for a limited set of geometric rules; report accuracy.

10) Data Governance, Open Data, and Responsible AI for City Operations

What it is & why it matters
Open data platforms and citywide data governance frameworks turn raw streams into public value—better services, accountability, and innovation—while protecting privacy. Standardized KPIs let cities compare progress across sectors and peers.

Requirements & low-cost alternatives

• Core: Data inventory, classification policy (public/internal/sensitive), privacy impact assessments, an open portal, and training.
• Nice-to-have: City KPI frameworks, data-sharing agreements, de-identification pipelines, and a review board for AI use.
• Low-cost start: Publish three high-value datasets with documentation; adopt a simple DPIA template.

Step-by-step

1. Establish governance roles and a lightweight approval workflow.
2. Stand up an open portal with machine-readable datasets and APIs; create a feedback loop.
3. Choose a city KPI set (service performance, quality of life) and publish a dashboard.
4. Pilot responsible AI for one use-case (e.g., pothole detection from imagery) with bias and accuracy reviews.
5. Expand through partnerships with local universities and civic tech groups.

Beginner modifications & progressions

• Simplify: Static CSV releases with clear metadata.
• Scale up: Event streams, data trusts, privacy-preserving linkage across departments.

Recommended metrics
Datasets published, API calls, reuse in apps/research, privacy incidents (target: zero), and share of programs reporting against KPIs.

Safety, caveats, mistakes to avoid

• Publishing sensitive data by mistake; insufficient consent and minimization; weak audit trails; AI deployed without human oversight.

Mini-plan

• Launch: A portal with mobility, permits, and budget datasets.
• Govern: Approve a short data policy and DPIA checklist; train staff.

Quick-Start Checklist (Urban Infrastructure Tech)

• Pick two pilots (one operations, one capital) with strong baselines and visible benefits.
• Define 3–5 KPIs per pilot and commit to before/after measurement.
• Confirm connectivity (fiber/5G/LPWAN) and power for field equipment.
• Establish data governance (roles, classifications, DPIAs, retention).
• Include cybersecurity requirements in RFPs (network segmentation, encryption, patch cadence, incident response).
• Write a change-management plan (training, SOPs, union engagement).
• Communicate public benefits in plain language and multiple languages.
• Schedule 30-, 60-, 90-day reviews for course correction.

Troubleshooting & Common Pitfalls

• Pilot purgatory. Fix: Pre-define “go/no-go” thresholds and a funding path for scale-up.
• Data silos. Fix: Mandate APIs and schema alignment; appoint data stewards.
• Over-sensoring. Fix: Instrument the problem, not the map; prioritize high-variance locations.
• Security debt. Fix: Baseline OT/IT inventories; enforce patch and key rotations.
• Equity gaps. Fix: Co-design with affected neighborhoods; build offline and multilingual channels.
• Vendor lock-in. Fix: Require open standards, data export rights, and exit plans in contracts.
• Weak baselines. Fix: Spend two weeks measuring before flipping any switches.

How to Measure Progress (and Prove It)

• Mobility: Travel time index, buffer index, crashes per million vehicle-km, bus on-time performance, person-throughput per lane.
• Energy: EUI (kBtu/m²-yr), peak kW shaved, outage minutes, microgrid uptime, DR events met.
• Water: NRW volume (m³/day), leaks fixed per km, overflow events, energy/m³ pumped.
• Waste: Overflow incidents per 100 bins, route miles per ton, diversion and contamination rates.
• Connectivity: Uptime, fiber miles added, percent of assets on redundant paths, IoT device onboarding time.
• Resilience: Warning lead time, message delivery rate, shelter activation time, restoration time.
• Permitting: Median days to decision, resubmittal rates, digital submission share, satisfaction.
• Data: Datasets published, API usage, privacy incident count (target: zero), programs reporting against KPIs.

A Simple 4-Week Starter Roadmap

Week 1 — Baseline & pick pilots

• Select one corridor for ITS and one municipal building for energy automation.
• Capture before-data and confirm connectivity and power at all device locations.

Week 2 — Procure & prep

• Issue quick-buy orders for sensors/controllers aligned to open standards.
• Stand up minimal dashboards; finalize SOPs and change-management steps.

Week 3 — Deploy & train

• Install adaptive signal control and TSP on the pilot corridor.
• Implement building scheduling, setbacks, and submetering; train operators.

Week 4 — Operate & report

• Run the first DR/curtailment event and log response.
• Publish before/after data for the corridor; gather public and staff feedback.
• Decide: scale, pivot, or stop—then lock the next 60-day plan.

FAQs

1) Where should a city start if resources are limited?
Pick one corridor and one facility. Prove results with clear KPIs and invest savings into the next phase.

2) How do we avoid vendor lock-in?
Specify open standards (e.g., open data formats, openBIM where relevant), require data export rights, and include an exit plan in contracts.

3) What about cybersecurity for all these connected devices?
Segment networks, use strong authentication and encryption, update firmware regularly, and run tabletop exercises for incident response. Treat OT like critical IT.

4) How do we protect resident privacy?
Adopt data minimization and purpose limitation, run privacy impact assessments, de-identify at source when possible, and provide accessible notices and opt-outs where appropriate.

5) Our legacy systems are old. Can we still modernize?
Yes. Use gateways and adapters to bridge protocols, prioritize replacements at failure points, and stage upgrades by district or asset class.

6) How do we fund these projects?
Blend capital budgets, performance-based contracts, utility programs (for DR/efficiency), and grants. Start with pilots that generate savings to reinvest.

7) What KPIs matter most to elected leaders?
Travel time reliability and safety for streets; outage minutes and DR savings for energy; leak volumes for water; overflow incidents and diversion for waste; permit turnaround time; and clear, public dashboards.

8) How do we ensure equitable outcomes?
Co-design with communities; target early investments in underserved neighborhoods; measure benefits by geography and demographics; publish results.

9) What if pilots don’t deliver the promised ROI?
Analyze root causes—measurement error, wrong location, configuration, or unrealistic assumptions—and either retune or stop. Publish lessons learned to build trust.

10) How do we scale beyond pilots?
Codify standards and playbooks, align procurement to those standards, schedule quarterly rollouts, and keep one cross-department program office accountable for KPIs.

11) Can AI help, or is it hype?
AI can forecast demand, detect anomalies, and classify images for maintenance. Use it where you have labeled data, clear success criteria, human oversight, and a risk review.

12) What timeline is realistic for visible results?
Signal retiming and TSP can deliver within weeks; basic building tune-ups within a month; water DMAs within a quarter; larger capital projects take longer but benefit from early design decisions informed by data and digital twins.

Conclusion

Urban infrastructure is no longer just concrete and cables—it’s a living network of assets, data, and people. The cities that win will start small, measure outcomes, protect privacy, and scale what works. With focused pilots, open standards, and rigorous KPIs, technology becomes a lever for safer streets, resilient energy, clean water, efficient services, and public trust.

Call to action: Pick one corridor and one building this month—measure, modernize, and share the results.

References

• 68% of the world population projected to live in urban areas by 2050, United Nations, 2018, https://www.un.org/uk/desa/68-world-population-projected-live-urban-areas-2050-says-un
• Urbanization, Our World in Data, 2024, https://ourworldindata.org/urbanization
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• Climate Change (Urban areas share of CO₂ and energy use), UN-Habitat, n.d., https://unhabitat.org/topic/climate-change
• Urban Climate Action: Urban Content of the NDCs (cities’ share of emissions/energy consumption), UN-Habitat, 2022, https://unhabitat.org/urban-climate-action-the-urban-content-of-the-ndcs-global-review-2022
• World Cities Report 2024: Cities and Climate Action, UN-Habitat, 2024, https://unhabitat.org/world-cities-report-2024-cities-and-climate-action
• Bridging infrastructure gaps: Has the world made progress?, McKinsey Global Institute, 2017, https://www.mckinsey.com/capabilities/operations/our-insights/bridging-infrastructure-gaps-has-the-world-made-progress
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• Travel Time Reliability: Making It There On Time, All The Time, FHWA, 2017, https://ops.fhwa.dot.gov/publications/tt_reliability/ttr_report.htm
• ITS Deployment Evaluation: Benefits, U.S. DOT ITS JPO (ITS Knowledge Resources), updated 2025, https://www.itskrs.its.dot.gov/benefits
• Evaluation Resources (ITS Deployment Evaluation Program), U.S. DOT, 2024, https://www.transportation.gov/sites/dot.gov/files/2024-04/Evaluation%20Resources_2024-04-19.pdf
• Benchmark Your Building With Portfolio Manager, ENERGY STAR, n.d., https://www.energystar.gov/buildings/benchmark
• What is Energy Use Intensity (EUI)?, ENERGY STAR, n.d., https://www.energystar.gov/buildings/benchmark/understand-metrics/what-eui
• U.S. Energy Use Intensity by Property Type (Technical Reference), ENERGY STAR, Aug 1, 2024, https://portfoliomanager.energystar.gov/pdf/reference/US%20National%20Median%20Table.pdf
• Using digitalisation in emerging markets and developing economies to enable demand response in buildings, International Energy Agency, July 10, 2023, https://www.iea.org/reports/using-digitalisation-in-emerging-markets-and-developing-economies-to-enable-demand-response-in-buildings
• Demand Response (definition and role), International Energy Agency, n.d., https://www.iea.org/energy-system/energy-efficiency-and-demand/demand-response
• Digital Demand-Driven Electricity Networks Initiative, International Energy Agency, n.d., https://www.iea.org/programmes/digital-demand-driven-electricity-networks-initiative