Engineering Solutions For Smart Cities

In countries like the Netherlands, trash doesn’t just disappear — it goes underground. How is it organized in your city? Amsterdam, Rotterdam and Utrecht use underground waste containers and smart collection systems where bins are connected to large subterranean units, keeping streets visually clean, reducing odour, and cutting unnecessary truck movements. But this isn’t just a Dutch story. It’s a global shift powered by technology. 📊 How leading cities are transforming waste management: 🇳🇱 Netherlands • Underground containers reduce surface bin clutter by up to 70–80% in dense neighbourhoods • IoT sensors monitor fill levels, enabling 30–40% fewer collection trips 🇰🇷 Songdo, South Korea • Fully pneumatic waste system • Trash travels through underground vacuum tubes at 70 km/h • Eliminated traditional garbage trucks in residential zones • Reduced waste handling costs by up to 50% 🇳🇴 Bergen, Norway • Pneumatic underground network beneath historic districts • Cut CO₂ emissions from waste collection vehicles by up to 35% • Reduced noise pollution in heritage zones 🇸🇬 Singapore • Smart bins + centralised waste chutes in HDBs • Waste-to-energy plants process over 90% of Singapore’s waste, shrinking landfill dependency • Semakau Landfill projected lifespan extended from 2045 to beyond 2035 through tech & efficiency gains 🚀 Technology making this possible: • IoT sensors for real-time bin monitoring • AI-powered route optimisation reducing fuel use • Pneumatic vacuum tube networks • Automated robotics for waste sorting • Waste-to-energy conversion systems ✅ The impact: • Cleaner cities • Fewer pests and odours • Reduced emissions • Lower operating costs • Better citizen experience The future of urban living isn’t just about shiny skyscrapers — it’s about invisible infrastructure working intelligently beneath our feet. Smart cities aren’t just built. They’re engineered to stay clean. #SmartCities #UrbanInnovation #Sustainability #CircularEconomy #CleanTech

Rain gardens are nature-based solutions to manage stormwater, enhance biodiversity and public space A rain garden is a shallow, vegetated depression designed to capture and absorb rainwater runoff from impervious surfaces like roofs, roads, and pavements. Filled with native plants, engineered soil, and gravel layers, rain gardens slow down and filter water through the ground, reducing pressure on urban drainage systems and improving water quality. These systems support urban resilience by mitigating flood risks, recharging groundwater, and creating habitats for pollinators and other species. Rain gardens also cool the microclimate, absorb pollutants, and offer visually attractive green pockets in dense urban settings. They are commonly integrated into residential areas, streetscapes, and public parks as part of sustainable urban drainage systems (SUDS). #RainGarden #GreenInfrastructure #StormwaterManagement #UrbanNature #SustainableLandscapes #NatureBasedSolutions #ClimateResilience #Biodiversity #LandscapeArchitecture

Wrapped up my latest visit to New York City, and it reaffirmed a vital truth: the iconic skyline, while breathtaking, also represents a significant carbon challenge. As buildings contribute over two-thirds of NYC's emissions, their transformation is crucial to achieving the ambitious 2050 goal of an 80% reduction.   Digital technologies offer a feasible and cost-effective solution. Consider these numbers:   Digital building management alone can achieve 42% emission reduction in offices, with payback periods of less than three years. Electrification and microgrids with renewable energy sources can further reduce emissions by 28%.   The combined impact? 70% reduction in operational carbon emissions. Achievable today, with a quick return on investment.   Now, imagine the impact at scale: New York City's iconic skyline, gleaming with clean energy. Let's make it a reality.

This is a fantastic example of modern geospatial analytics in action. A new paper from Andreas Christen and the team at the University of Freiburg demonstrates how AI can help cities balance two competing goals: urban densification and heat mitigation. The real power here lies in the orchestration of multiple complex datasets to drive actionable insights. The study didn't just map temperature; it fused LiDAR point clouds, 3D semantic city models, and historical weather data into a unified AI workflow. Instead of traditional, computationally expensive physical simulations, they used AI models to rapidly predict "thermal comfort" at a hyper-local scale. This allows for: - Data Fusion: distinct datasets (geometry, vegetation, climate) working together. - Prescriptive Analytics: Moving beyond descriptive maps to automated optimization identifying exactly where to plant trees or place buildings for maximum cooling. It’s a glimpse into the future of urban planning, where geospatial data and AI doesn't just describe the problem, but actively designs the solution. Congrats to the team and great paper/read! Read the paper here: https://lnkd.in/eqBCym9Z 🌎 I'm Matt Forrest and I talk about modern GIS, earth observation, AI, and how geospatial is changing. 📬 Want more like this? Join 12k+ others learning from my daily newsletter → forrest.nyc

🚀 Accelerating Industrial Digitalization and Intelligence: Transforming Integrated Operation Centres with Digital Twins As the Technical Director of the EU Local Digital Twin EU LDT Toolbox - Empowering Smart Cities Initiative under the European Commission, I am thrilled to share how Digital Twins are reshaping integrated operation centres, driving urban management into a new era of intelligence and efficiency. 🌍✨ Digital Twins are a convergence of groundbreaking technologies: ✅ 5G Advanced & IoVT: Real-time data collection from connected devices and video sensors. ✅ Data Spaces: Seamless integration of utilities, socio-economic stats, and human dynamics for actionable insights. ✅ AI/ML & GenAI: From event detection and predictive analysis to user-friendly reports that make data accessible to all. ✅ Geospatial Technologies: AR/VR, 3D mapping, and GeoAI enabling immersive, actionable insights. ✅ Advanced User Interfaces: Bridging technology with usability through the Citiverse. 💡 Real-World Impact: These technologies are not just concepts—they are actively transforming urban centers, we are presenting a real example in Shenzhen, China by Huawei; which is addressing: 🌳 Enhancing sustainability with smarter green coverage and air quality monitoring. 📊 Improving economic operations by integrating socio-economic data to optimize investments and retail strategies. 🎥 Boosting safety and efficiency through IoVT and real-time event detection, such as traffic violations or public safety hazards. 🛠 Driving job creation by turning AI-detected events into actionable interventions, fostering local employment. The future is here, and it’s intelligent, sustainable, and immersive. By leveraging Digital Twins, we are creating smarter, greener, and more inclusive cities. Let’s connect to explore how we can drive the digital transformation of urban spaces together! 💬 #DigitalTwins #SmartCities #IndustrialDigitalization #UrbanInnovation #TechForGood #DataSpaces #AIForCities #Libelium

🚀 AlphaEarth Foundations (AEF) - New from Google DeepMind I keep looking out for interesting usecases of AI. Deepmind folks are at it again. 📄 Paper: AlphaEarth Foundations on arXiv (https://lnkd.in/giHUwe2d) --- 🌍 What is AlphaEarth Foundations? AEF is a foundation model for Earth observation that turns sparse and messy satellite, climate, LiDAR, and even text data into dense embeddings at 10 m² resolution. These embeddings provide a universal feature space for mapping and monitoring the planet, outperforming all previous approaches — reducing mapping errors by ~24% on average. And the best part? The embeddings are already available as annual global datasets (2017–2024) for free: 👉 Earth Engine Data Catalog: Google Satellite Embedding V1 Annual - https://lnkd.in/g6dcv4-M --- 🛠 Why does this matter? (weekend project ?) For places like Bengaluru, India (or any fast-changing city), AEF makes it possible to: - Track urban growth and land use change with very few ground samples. - Monitor lakes and wetlands for encroachment and seasonal changes. - Map flood risk by combining rainfall, elevation, and land cover. - Identify urban heat islands and vegetation loss. - Support peri-urban agriculture with low-shot crop type classification. - Study biodiversity shifts (tree species, invasive plants) by linking with GBIF/iNaturalist data. In short, it’s like having a plug-and-play geospatial backbone — ready to support everything from city planning to climate adaptation. --- 🔧 For the Geeks Want to try it out? You can get started in minutes using Earth Engine + Python: 📘 Earth Engine Python Quickstart Docs - https://lnkd.in/g9zBBPJv 🌐 This is a big step toward planetary-scale AI for environmental monitoring — making high-quality maps possible even when labels are scarce. --- Further reading : 1. https://lnkd.in/gsXU2BqS 2. https://lnkd.in/gxJpqS6b --- Authors: Christopher Brown, Michal Kazmierski, Valerie Pasquarella, William J. Rucklidge, Masha Samsikova, Chenhui Zhang, Evan Shelhamer, Estefania Lahera, Olivia Wiles, Simon Ilyushchenko, Noel Gorelick, Lihui Lydia Zhang, Sophia Alj, Emily Schechter, Sean Askay, Oliver Guinan, Rebecca Moore, Alexis Boukouvalas, Pushmeet Kohli.

This publication means a lot to me. After years of witnessing the difficulties cities and regions face in identifying their #ClimateRisks for #ClimatePlanning, we decided to create a detailed guidebook. 🌦️🌆 It offers a step-by-step process in an original way, following a fictional city as a case study, as well as real-life examples, and several FAQ highlights. 🎯A key innovation in this guidebook is the section on setting #AdaptationGoals, complete with practical targets and indicators to track progress over time. 🔗 Take a look here: https://lnkd.in/dPA8mj-v Feel free to share it with your network and let us know your feedback. Valentina Palermo, Gema Hernández Moral, Paulo Barbosa, Giulia Melica EU Covenant of Mayors, Global Covenant of Mayors for Climate & Energy (GCoM), EU Science, Research and Innovation #ClimateAdaptation #Resilience #RiskAssessment #ClimateAction

AI is now turning decades of "fragmented reports" into a foundation for global resilience. For many climate hazards, the high-fidelity historical data needed to train predictive models simply didn't exist. Today, Google Research is introducing Groundsource to bridge that gap. While we are starting with urban flash floods, the broader opportunity is to create a rigorous scientific baseline for hazards that traditional sensors often miss. By using Google Gemini to synthesise over 25 years of public information in 80 languages, we’ve demonstrated a scalable way to turn unstructured history into actionable intelligence. How this AI-driven methodology scales climate adaptation: 🧩 Solving the Data Gap: It creates a "ground truth" for regions lacking physical infrastructure, ensuring that no community is left behind in the era of AI-driven resilience. 🗺️ A Scalable Blueprint: This framework is a catalyst; while we've mapped 2.6 million flood events, the same methodology can be applied to landslides, heat waves, and other climate-related threats. 🔮 Predictive Power: This research is already powering 24-hour lead times for flash flood alerts on Flood Hub, giving cities a critical head start. By open-sourcing this benchmark, we are inviting the global sustainability community to help turn the records of the past into a more resilient future. https://lnkd.in/eSRvneuE #ClimateResilience #Sustainability #GoogleResearch #FlashFlood #Gemini #Adaptation

Unlocking the Power of GeoAI: From Raw Geospatial Data to Actionable Insights GeoAI is fundamentally changing the way we work with geospatial data. Today, artificial intelligence is not just a research topic, but a practical tool that helps us turn massive amounts of aerial imagery and lidar data into real, actionable information. By combining neural networks with proven photogrammetry and rule-based quality assurance, we can now extract detailed land cover maps, analyze urban surfaces, and even simulate urban climate with a level of precision that was unthinkable just a few years ago. One of the most exciting aspects is how GeoAI enables us to move beyond traditional mapping. With AI-powered segmentation, we can distinguish even the smallest features in urban environments and keep our data up to date. Thanks to TrueOrthos and advanced photogrammetric workflows, geometric distortions are a thing of the past, so data from different times and sensors can be perfectly aligned. This is essential for reliable change detection and multi-source analysis. But the possibilities go even further. Automated analysis of sealed and unsealed surfaces helps cities identify where to prioritize “desealing” for climate resilience. Parcel indexing allows us to aggregate key indicators like green space, building area, or solar installations at any scale, supporting truly data-driven decisions in urban planning and environmental monitoring. And with urban climate simulation, we can combine pixel-precise land cover data with 3D voxel models and CFD to visualize the effects of new trees, green roofs, or lighter pavements, before any construction begins. Even lidar point cloud classification benefits from GeoAI. By combining AI with rule-based checks and external data sources, we achieve robust, scalable, and quality-assured 3D mapping, reducing manual effort and increasing reliability, even in complex or changing environments. GeoAI is already a productive, scalable approach that is shaping the sustainable, data-driven development of our cities and landscapes. With annual updates and hybrid workflows, we ensure that results are not only precise and up to date, but also trusted and actionable. If you want to learn how to turn your geospatial data into valuable information using GeoAI, just reach out or send me a message. Let’s move from data to information, using GeoAI. 💡 Comment | Like | Share   👉 Follow me (Dr. Uwe Bacher) for more Information on exciting topics from the world of geospatial #GeoAI #Geospatial #AerialImagery #Lidar #UrbanPlanning #AI #SmartCities

Regenerative cities aren't just a vision. Concrete projects are already delivering them, meeting real technical, financial and social challenges. This week at ChangeNOW, I shared what this looks like in practice. Our starting point: a city that adapts to climate, social and resource pressures. Adaptation is no longer a bonus, it is the new standard for urban development. In practice, this means regenerating rather than expanding.  • In Orly-Thiais, we turned a 14-hectare industrial brownfield into a mixed-use district where green spaces went from 7% to 40%, with 2,600 homes and on-site rainwater management.  • In Tours, our Kipolis project reduced impermeable surfaces enough to handle a 100-year rainfall event.  • In Amsterdam, Equans installed a geothermal system at Schiphol Airport that cuts heating and cooling needs by 60%. These projects don't happen without strong public-private partnerships. Bouygues is not just a contractor: We are a long-term transformation partner for public authorities. Because none of this scales without collective ambition. #Bouygues4Resilience