Electricity should not only be produced more sustainably, but also used more efficiently to reduce overall consumption. AI (Artificial Intelligence) can help by using machine learning algorithms to detect and regulate energy consumption in homes and buildings through sensors. The system adjusts to the habits of the residents and reduces energy consumption through intelligent networking of systems. For hotels, indoor swimming pools, factories and office buildings, control devices can also help to match the measured data that have already been recorded with energy efficiency management systems. Intelligent controls thus reduce energy consumption, CO2 emissions and cost.

A popular application in renewable energy is in the management of solar panel systems. Solar panels are often installed in remote locations, making it challenging to monitor their performance. However, embedded software solutions with real-time monitoring capabilities can track the energy generation of each panel and provide insights into their efficiency. This information can be used to optimize the performance of the solar panel system and improve energy generation. By analyzing weather patterns, the system can also predict and prepare for any drop in energy generation, ensuring a continuous supply of clean energy.

Smart grid technology is used to monitor and control energy distribution in real-time, optimizing energy use and reducing waste. With sensors and computer algorithms, smart grids can detect changes in energy demand and dynamically adjust energy production and distribution to meet changing needs. This results in a more efficient, flexible, and resilient energy system.

More and more animal species are threatened worldwide and populations are shrinking. To counteract this, effective measures must be taken for their sustainable protection. However, in order to know how many animals are still around and the ways in which they spread, enormous efforts have had to be made so far. In many countries, such as China, conservation organizations are therefore using AI (Artificial Intelligence) to analyse thousands of daily taken photographs coming from automatic photo traps. In the past, the countless photos had to be evaluated and sorted individually by humans. Today, this can be done by cloud technology, which sends the images directly to the experts for evaluation. In advance, animals are identified by their own characteristics, such as coloring, stripes or size, so that the species can be better separated from each other. In this way, enormous amounts of data can be pre-sorted, catalogued in a data base and displayed in a geological animal spreading overview with countries and regions.

Weather monitoring and climate prognosis play a crucial role in predicting and mitigating the effects of extreme weather events, like hurricanes, droughts, and heat waves. These systems use various technologies, such as satellites, radars, and weather stations, to gather data on the current weather conditions and forecast future trends.

Satellites, for example, provide a broad view of weather patterns and conditions by capturing images and data from high above the Earth's surface. These images and data are then used to create weather maps and models in real-time, which can be used to forecast future weather patterns and conditions. Weather stations provide ground-level data on current weather conditions, such as temperature, wind speed, and precipitation. This data is used to create local weather forecasts and to monitor and predict weather events.
 

Drought and dryness are increasing worldwide and affect forests, fields and meadows. This increases the risk of fires enormously. Early detection of forest fires can significantly reduce the extent of damage and save lives. Today, the most modern technology is used for this purpose. Therefore, towers are used that can automatically detect and report fire hazards in the surrounding area with an optical early warning system. By means of a 360-degree panorama sensor, a radius of up to 15 km is recorded and the presence of smoke features analyzed in real-time. This way, fires can be detected at an early stage and reported via radio signal or DSL to a control center, which can then notify and coordinate the appropriate emergency services. And even further, drones can be sent out automatically to monitor the area and direct emergency groups to the fire.

Humanity needs more and more food, and producers face daunting tasks. With better and more accurate data, farmers could grow food more efficiently and with less environmental impact, depending on the region or climatic conditions. Data from satellites, drones, tractors and sensors can be fed into cloud-based artificial intelligence models to provide a digital picture of soil quality in fields. A network of sensors measures soil acidity, moisture and temperature, while a weather station collects important data such as wind speed, precipitation or air temperature. The tractor provides insights into the biomass and its characteristics, such as growth height and coloring, which are indicators of plant health. All this data can be generated into overviews that can be used to target seeds or fertilizers and refine cultivation methods, resulting in higher yields, fewer failures, lower costs and more sustainable agriculture.

What used to be manual work can now happen automatically. Today's agriculture means precision work. In order to apply seed or fertilizer precisely, a field is flown over with a drone beforehand and the results are syncronized with connected sensors in the earth. All data are then analyzed and sent to an automated tractor that automatically drives over the field and delivers nutrients to where they are needed. The great advantage of this interconnected drone and sensor digitalization lies in the efficient control of where and how much of a substance is used, reducing emissions (CO2 emissions) and strengthening sustainable farms economically for the future. This also minimizes the impact on the environment and generates more profit from the resources used (men power, time and cost for pesticides, nutrients and seeds).

With precision farming, significant savings in agriculture can be achieved in terms of labor time, machine hours and farming supply inputs. This also includes the use of crop protection products and fertilizers for a more sustainable product and environmental quality. The use of high-tech for the digitalization of agriculture (digital analyses, connected agricultural machinery or processing plants) will lead to considerable savings in input quantities in Agriculture 4.0, according to specialists.

In agriculture 4.0 the use of milking robots in a cowshed is a way to improve efficiency, productivity, and cow comfort as these robots are designed to automate the milking process, freeing up time for farmers to focus on other tasks and allowing cows to be milked on their own schedule. Milking robots use sensors and computer algorithms to identify individual cows and attach the milking apparatus. The cows are then milked without the need for human intervention. This results in a more relaxed and stress-free environment for the cows, which can improve their overall health and milk production. In addition, milking robots can also provide valuable data on cow behavior, health, and milk production allowing farmers to make informed decisions about herd management and improve the overall efficiency of their operation.

Real-time monitoring of water resources is critical for effective water management. Advanced sensors and control systems can be integrated into the water distribution network to monitor flow rates, water pressure, and other key parameters in real-time. This data can be used to optimize the water distribution network, reducing waste and improving overall efficiency. With real-time capabilities, water managers can quickly respond to changes in demand and make informed decisions to ensure that water resources are used sustainably. Additionally, real-time monitoring of water quality can help to prevent contamination and ensure that the water supply remains safe for consumption.

Our environment is suffering from garbage and plastic. Millions of tons of garbage end up in nature and are also reaching our coasts and oceans. And with that, the concentration of microplastics is increasing year by year. To solve that problem, swimming drones can be used in canals, lakes and rivers to collect swimming garbage. They can be powered via battery or solar modules. Remote control could also be possible or it operates autonomously, scanning the surrounding, collecting the garbage and then return back to its base. Furthermore, it can collect data by analyzing the depth, temperature, pH and salinity of the water for later evaluations of the affected area.

Technology can be used to monitor water quality in real-time, providing information on water temperature, pH, dissolved oxygen levels, and other key parameters. This information can be used to identify areas of concern and take action to improve water quality and protect aquatic life.

With the use of remote sensing technologies such as drones and satellites, it is possible to monitor changes in coastline and coastal erosion, providing important information for decision making and coastal management.

This topic refers to the use of technology and real-time data to monitor, analyze and control air pollution in urban areas. It involves the integration of various sensors, IoT devices, and big data analytics to gather information on air quality, including PM2.5, PM10, and CO2 levels. This data is then used to develop actionable insights and inform decision-making to improve air quality. The goal of smart city air quality management is to create healthier, more sustainable and livable urban environments for residents. It also helps in reducing health risks associated with air pollution, improving air quality for the environment and increasing the overall quality of life for citizens.

Real-time air quality data can help to optimize traffic management systems and reduce emissions. For example, the data can be used to re-route traffic away from heavily polluted areas or to adjust the speed limits of vehicles to reduce emissions. The monitoring can also include analysis of the air quality in and around public places: Schools, hospitals or transportation hubs, such as airports and train stations, to reduce exposure to harmful pollutants.