Most chances you had the pleasure of eating a watermelon this summer. Most chances it was also sweet and delicious. Have you ever considered where, this wonderful fruit containing 94% water is getting all of its liquids? With no intention of spoiling your next watermelon treat, know that most likely it obtains its liquids from effluent waters treated in wastewaters treatment facilities. Dozens of such facilities are scattered around Israel and the water that were used to irrigate your watermelon probably came from such facility.

Israel is the leading country in recycling of effluent waters. Over 90% of our flushed waters are being recycled. Recycling effluent waters have clear economic, environmental and health benefits. However, too often, wastewaters are contaminated with pollutants, thus affecting the quality of the treated wastewaters and affecting, through the soil, on our vegetables and fruits.

Pollution of wastewater is a global concern. Pollutants are responsible for many health issues and reduce the amount of available clean waters, an increasingly sought out natural resource. Wastewater treatment facilities can perfectly treat sanitary sewage, which constitute 95% of all effluent waters treated. However, the remaining 5%, originating from industrial plants, are the major source for pollutants. The pollutants not only affect the quality of the water used to irrigate our fields or the water quality of our rivers and Oceans, but also contaminate the sewage sludge (an important byproduct of effluent water treatment) used to fertilize agricultural lands.

There is a saying that “A fool may throw a stone into a well which a hundred wise men cannot pull out.” Indeed, to prevent wastewater pollution, we need to detect and prevent it upstream, at its source. The only practical solution is using water-monitoring technologies. Unfortunately, the field of effluent monitoring is just starting to rouse after years of stalemate, after being overlooked for decades.

Nowadays, water utilities divert much more of their attention to the field of effluent and wastewater treatment for various reasons. Such reasons might be: the increasing importance of water as a natural resource, industrial effluent rules and regulations, criminal accountability of treatment facilities and the water utilities, environmental responsibility and of course, money. A lot of money. More than 500 billion USD are going to be invested in effluent and water infrastructures, in the U.S and Europe alone. Research institutes are predicting that up to 20% of the infrastructure cost will be saved, if the water companies and corporations will assimilate advanced technologies.

The water utilities, desperately seeking out advanced assets management, “smart city” applications and new technologies, are embracing sewage networks management solutions. Unfortunately, accurate real time monitors are very expensive and demand hard labor. The high cost creates a dilemma; the use of sensors able to detect precisely a pollutant requires costly monitoring units, which prevents citywide deployment. Cheap units, on the other hand, can detect only a fraction of industrial pollutants.

The use of algorithmic and machine learning techniques in the field of effluent pollution monitoring is a solution that has the potential to revolutionize the field since it can provide both high resolution detection and a wide monitor deployment at a low cost. Continuous monitoring using cheap, simple and available sensors combined with various databases and lab test results introduces a new and exciting field of analytics.

Using lab result databases, historic data sets from various sectors or industrial plants and other variables, each plant or monitored site can be uniquely profiled, thus allowing creating exact correlations, which extract high amount of data from sensors readings. Ultimately, this will allow predictions of lab test results and detect patterns or anomalies in the sewage network. Since this technology relies on computational power of software rather than hardware, a wide deployment of neuron-net style monitors in the “smart city”, able to communicate with one another and independently real-time decision making is possible.

Thus, by online detection of pollution, anomaly detection and pinpointing a pollutant in a “big brother” style via machine learning; the client gains important insights, which eventually save him millions of dollars and billions of cubic meters of water.

The direction to which this market is heading is clear. Like all “smart city” applications, the water utilities are interested in getting real time databased insight. Even today, a dramatic decline in effluent pollution levels is reported by many water utilities due to such affordable, smart, real time monitoring technologies.

The technology is the shield of wastewater treatment facilities, assuring the quality of the treated water irrigating your watermelon or discharged to your rivers and seas.

So next time you eat a watermelon, remember that someone is looking after you.