blog Environmental observations are a building block in sustainable and smart cities Share Aviation and Road Solutions Sustainability Weather & Environment As cities grow, so does also the number of people subjected to the environmental conditions in urban areas. According to the UN, it is projected that by 2030 the number of people living in cities will rise to 5 billion. Concentration of population, traffic, and industrial processes bring on changes in weather and environmental conditions, such as air quality. To tackle these challenges, the UN Sustainable Development Goal (SDG 11) Sustainable Cities and Communities aims to provide access to safe and sustainable transport as well as reduce the adverse environmental impact of cities, for example. With Vaisala’s solutions, decision-makers can gain data on road and urban weather as well as air quality, which supports decisions concerning the well-being and safety of citizens. Vaisala helps smart cities to overcome their challenges with urbanization and make informed decisions regarding sustainability, economic growth, safety, and well-being. Our reliable instruments, systems, and digital solutions measure air quality and road weather as well as urban weather and microclimates in urban areas. Poor air quality is the most serious environmental health issue globally and depends also on meteorological conditions. Vaisala combines data from high performing air quality sensor networks with important weather measurements, which helps to forecast air pollution. The local air quality monitoring networks and weather data help authorities to pinpoint and manage the problem areas, especially in cities, and make important decisions concerning air quality. Environmental and weather measurements are key factors also for traffic in cities. The accurate and local information on weather conditions and road state from Vaisala’s instruments help ensure safe traffic flow. Sustainable and smart city development, automation, and digitalization change traffic and the modes of transportation. For instance, autonomous vehicles require ever more accurate environmental observations; observations and analyses on the environment and road state enhance the safety and efficiency of traffic in different conditions. Road weather and condition monitoring: enabler of smart and safe traffic in cities Urban environments consist of road networks, both large and small. To ensure safety, it is critical for transportation and roads operators to monitor the current conditions on roads in and highways leading to cities. Vaisala provides solutions that combine measurement technologies, computer vision, forecasts, and open data, providing authorities with the information they need. Based on that data, they can make informed decisions and ensure the safety and efficiency on road, rail, sea, and air. Vaisala provides the data both through its static road weather stations as well as mobile computer vision software installed in moving vehicles to assess weather and road conditions. Road weather information is the key to successful decision-making. Weather responsive traffic management helps make informed operational decisions to keep road networks safe and traffic flow optimal – even in the most extreme weather conditions, such as winter, low visibility, flooding and high water, high winds, and sand storms, for example. Road weather stations give an overview of the areas that are facing difficult road weather conditions, which enables operators to provide alerts for drivers. The data from road weather stations can be combined together with the real-time mobile data that Vaisala’s MD30 mobile detectors gather, installed in moving vehicles – for example postal delivery and maintenance vehicles. In RoadAI software, computer vision analyzes the visual video data automatically, and it is presented in the RoadAI portal, where road authorities can assess the state, condition, and maintenance needs of the road network. Combined with road weather model, heat maps, and information systems, this data helps to optimize road winter maintenance resources, for example. Timely decisions on anti-icing, de-icing, and snow ploughing increase safety and resource efficiency as well as reduce the environmental effects of chemicals used in road maintenance. ? Computer vision solutions extend Vaisala’s offering to collecting and managing data on road surface condition. Potholes and cracks are identified quickly and accurately to support repair planning and budgeting. The RoadAI software development, with computer vision and machine learning, are part of the work of the Vaisala Digital unit that was reorganized in the fall of 2019. The unit builds up enhanced competences in machine learning and artificial intelligence, which gain ever more importance in the future of developing weather critical information. Looking to the future, autonomous vehicles will depend on reliable data on urban and road weather as well as road condition monitoring. Computer vision software and road weather information are thus integral for autonomous vehicle developers. As traffic is becoming more and more autonomous in the future, it is of utmost importance to make sure the safety of the vehicles. With computer vision software, the vehicles are able to analyze road state condition and weather, adjusting the speed and driving accordingly. The software is also able to blur people and vehicles on the road to acknowledge citizens’ privacy. Whether we are discussing air quality or the weather-dependent traffic, Vaisala’s solutions can help transportation authorities and decision-makers make timely and informed decisions concerning the safety and well-being of citizens in various areas of urban development.*** This is the sixth post in our article series about Vaisala’s commitment to the UN Sustainable Development Goals. Vaisala’s multifaceted business is brimming with stories, and in this article series, we illustrate with concrete examples, how our business is truly linked to the SDGs. Stay tuned for more information on how our solutions, practices, and mission Observations for a better world reflect the goals. ?