Smart City Environment and Energy

The greatest savings in water consumption can come from automating agricultural and municipal use: More than 70 percent of water consumption today is for agricultural use, and 60 percent of the remainder goes to urban landscape maintenance.

In both instances, agribusiness companies often irrigate regardless of current conditions, risking overwatering rather than drought. Sensors with advanced algorithms can help address both problems, aggregating measurements of soil moisture, heat, humidity, and slope to analyze how much water plants need.

Traditionally, electricity has been generated by large-scale, conventional plants based on fossil fuels or nuclear power. A proportion of this will likely be displaced by distributed generation based on renewable energy sources such as solar panels or wind mills. Contrary to the current situation (few plants with very high capacity), this should lead to a situation where electricity is generated by a large number of nodes, of which many have a relatively small capacity.

In a truly smart city, a new class of smart citizens becomes prosumers, citizens who use homes and offices to generate electricity and consume the same. Buildings, increasingly covered with solar material and paper batteries, would transform the construction industry and create millions of new micro-sources of power.

Embedded sensors of various types are used for everything from pollution monitoring to land management, supplementing or replacing on-site inspections. Energy agencies rely on these sensors for continuous environmental monitoring and automatic intervention.

These technologies help agencies execute their missions but also raise issues concerning the definition and resolution of violations in a real-time monitoring environment. Embedded sensors in smart cities enable continuous monitoring of weather conditions, air quality, and home energy consumption.

Most cities use some type of waste container to collect the waste produced by households. Traditionally, these garbage trucks operated on fixed routes, e.g., visiting each container once a week. Consequently, some containers are emptied when they are only half full and some are emptied days after they became full.

The “smart” solution is to equip the waste containers with sensors that detect the volume of the waste in the container. This data is used to optimize the number of garbage trucks and their routes, skipping containers that are not yet full, and making an early stop at containers that are close to reaching their limit. This results in a cheaper process (fewer stops required) and elimination of full waste containers (which could lead to people dumping their waste on the street next to the container).

Water loss management is becoming increasingly important due to population growth and water scarcity. Experience shows that the amount of non-revenue water (water produced but lost due to theft, metering inaccuracies, and supply chain leakages) can be up to 25 percent.

To minimize this loss, water providers can equip the distribution network with sensors to provide real time insight on pressure, flows, and quality. By analyzing this data, especially the flows during night when normal consumption is minimal, leakages can be detected.

The data generated by smart meters can be used to create detailed insight into energy usage patterns. This data can be used by smart apps that use concepts like gamification to make consumers more aware of their energy usage and influence them to change their behavior to decrease their energy consumption.

Sensors can be used to measure the quality of surface water in real time. Traditionally, water-quality monitoring required manual actions for sampling and analyzing, causing a lag between the emergence of pollution and the detection of it. Real-time water quality monitoring, with a network of sensors covering surface water, contribute to sustainability of city resources.

Responsive, or “smart,” devices and appliances (e.g., air conditioners, hot water heaters, refrigerators, and clothes washers and dryers) can temporarily reduce energy consumption during peak energy demand periods. This “demand response” may be triggered by a signal from the utility during a peak demand event, or by intraday price increases in areas where local utilities provide dynamic, “time of use” pricing.

Customers control home energy usage automatically through devices like the Nest Learning Thermostat, which studies the habits and patterns of consumers to find the most optimal use of energy.

Electric utilities are adding IoT technologies such as sensors and automated controls and linking them to advanced communications and analytic software. The software monitors distribution-system data in real time and can detect and isolate faults and reconfigure the system to minimize impact on customers, with limited human intervention.

The grid can “heal” itself through a combination of automated switching, dispatch of distributed energy resources, and coordinated demand response and management without intervention by operators in the control room.

Smart meters record electricity consumption in intervals of one hour or less and communicate this data to the utility company. This allows utilities to introduce dynamic pricing based on the season and the time of day and encourages citizens of smart cities to reduce their energy consumption, especially when demand is at peak level.

Smart meters also provide data that helps utilities better monitor the health of the electric grid, restore service faster during outages, communicate information to customers such as high usage alerts, and integrate distributed energy resources.

Through better design and life-cycle thinking, consumption and production become closed loops, producing no outputs as waste throughout their life cycle. As such, the concept of waste disappears, as all byproducts retain an intrinsic value to feed into other systems. Even food spoilage and waste could be reduced to zero and turned into biofuels, compost, or animal feed.