AI in Indoor Water Conservation

GREYWATER RECYCLING

The leftover water from washing machines and kitchen and restroom sinks that has not been in contact with any fecal contamination can still be repurposed for secondary uses in the building. A strategically designed distribution system can collect greywater from the building to apply treatment, instead of directly entering it into the sewer. This recycled water can be put back in the building, becoming an additional source of water for non-potable purposes such as landscaping and irrigation, thus developing an alternative source for consumption and saving the limited freshwater source ¹⁴.

RAINWATER HARVESTING

Across climate zones and varying amounts of annual precipitation, the optimal shape and orientation of the building or collection of buildings and various horizontal surfaces can directly contribute to the efficiency of rainwater capture ¹⁵. It’s therefore extremely important to consider using the building form to maximize the amount of rainwater catchment – especially in drier climates – as early as the conceptual and schematic phases of the design process. An example of maximizing rainwater harvesting through design is the roof of The Edge in Amsterdam, designed by PLP architecture firm (Figure 6), which has created a reservoir for gathering the rainwater to supply the toilet water for the whole building as well as the garden irrigation need ¹⁶. The Specific geometry shape orientation, direction and the slope of the Edge building makes it possible to maximize the amount of rainwater harvesting. This building uses the collected rainwater for the flushing system of all their toilets as well as gardening the landscape.

LANDSCAPE AREA

In addition to harvesting rainwater from a building's roof, optimal locations for large-scale rainwater harvesting systems on the ground can be identified by combining various socio-environmental characteristics, such as elevation, slope, precipitation, temperature, distance from the river, land use, geology, soil type, population density, distance from roads, and lakes. Along with the use of artificial intelligence algorithms, these strategies can be incorporated into the site's landscape design¹⁸.

Actively designing to reduce the amount of turf area, while also considering using mulch and native plants, can reduce the amount of water needed for irrigation. Additionally, designers should consider using porous materials for any hard surfaces, such as permeable paving, which is a range of sustainable materials and techniques with a base and sub-base that allow the movement of storm water through the surface. In addition to reducing runoff, permeable paving effectively traps suspended solids and filters pollutants from the water. By allowing the water to seep into the ground, the direct and surrounding areas will need much less mechanical irrigation intervention, saving money and ultimately reducing the amount of water used for everyday irrigation needs.

WATER-EFFICIENT APPLIANCES

Using Energy Star-rated appliances in the building, such as dishwashers, washing machines, low-flow toilets, showerheads, and faucets, has been shown to reduce water usage, and in most cases resulting in at least a 20% water savings ¹⁹.

WATER QUALITY MONITORING

There are numerous chemicals in the water, some which can be harmful to our body, leading to many illnesses such as nausea, headache, vomiting, and even death. Therefore, it is vital to evaluate the quality of the water that we use ²⁰. Manually extracting water samples across multiple sites and then sending those samples to a lab for further testing costs time and money, and can result in delayed, point-in-time information. And because a manual extraction cannot sample the exact same location and depth each time, it’s also inaccurate. However, AI-based algorithms can be used to actively monitor water quality in buildings and track key metrics by analyzing sensor data to detect and alert potential issues such as contamination or bacterial growth. Additionally, AI can improve how water resources are managed, by training machine learning models to forecast water quality using water data from hydro-electric powerplants ²¹. Companies such as Saafwater, monitor water quality in real-time to forewarn anomalies, while also recommending purification methods to improve it. The platform also provides water quality forecasts to enable proactive safety measures ²².

FASTER MAINTENANCE

AI is also being leveraged by engineers and water management authorities to keep water equipment and pipeline networks in the right order and provide cost-effective maintenance solutions. Pipebots, a UK-based project, aims to develop AI-powered micro-robots to analyze the state of underground pipelines and affordably repair them. Similarly, IBM, a global technology company, has utilized AI and machine learning to develop an in-pipe inspection prototype named Sewer Spy to find erosion and corrosion of pipelines ²³. Emagin is another industry example using data analytics and machine learning to provide operators with the ability to make decisions and forecasting based on data from real-time sensors ²⁴.

LEAK DETECTION

Plumbing leaks can create a moist environment within buildings – an ideal situation for bacteria and mold growth – which have many negative health effects on occupants. AI algorithms can be used to analyze sensor data to detect leaks in plumbing systems, which can lead to significant water savings and prevent any health risks.  WaterSignal is currently one of the tools used in order to collect real time data of water usage of a building. This would help in water management and identifying any abnormal water usage, which can be a result of a leak ²⁵. Additionally, each fixture creates a unique type of sound frequency based on the water usage and flow. Phyn’s direct leakage detection technology through sound ²⁶ utilizes high-definition ultrasonic sensors to sample the pressure in the plumbing system 240 times every second. This produces an unparalleled view of the unique signatures of each fixture in the residential unit ²⁷.

IRRIGATION CONTROL

Currently, there are different type of irrigation methods for landscapes, the most tradition system is manually watering the garden area and the grass area, other methods include using sprinklers in the area, drip irrigation. However, all these methods are prone to error as the timing and the amount of the water usage are set by users. With the conventional methods, around 50% of the water in outdoor landscaping is wasted due to due to wind, evaporation, and runoff caused by inefficient irrigation methods and systems ¹⁹. To reduce this amount of waste, companies such as CloudRain ²⁸ and Eve ²⁹ have been employing novel AI-based algorithms to control optimizing irrigation water usage based on weather conditions, soil moisture, and plant needs.

WATER USAGE OPTIMIZATION

AI-based algorithms can be used to optimize the use of water in buildings, by controlling and adjusting the flow of water in real-time based on the occupancy and usage patterns collected from previous data points such as utility bills. Clustering the water consumption into different groups based on their main usage (e.g., toilet, sink, shower, etc.) can help to detect abnormal water usage in each area ³⁰.

USER BEHAVIOR

Achieving water consumption reduction goals requires the engagement of building occupants in the water conservation program, which is frequently one of the easiest and most affordable tactics to adopt. Currently, educational programs for improving the water usage of occupants inform users about the importance of water conservation and provide them with information and tools to reduce their water consumption with pamphlet distribution, incentive programs (such as water pricing), creating hot lines to report leaks, and displaying the water management to the public ³¹. AI-based behavioral change technologies can be used to promote energy savings in residential and office buildings. They can also understand the consumers’ demand and usage patterns for providing the most optimized response through controlling the flow of water in plumbing systems ³⁰. By combining IoT water micrometers in all water points with SaaS dashboard ³² to notify the user if the appliances were left on, data-driven transparency on water usage can be created. Using AI controllers for water appliances and pipes can lead to a considerable amount of energy cost saving ³³.