WWEM - Abstract

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Abstract Title: Wastewater Level Monitoring- the revolutionised way forward with IoT and Smart Machine-Learning Data Analytics
Presenter Name: Mr Asmir Hajric
Company/Organisation: Metasphere Ltd
Country: United Kingdom

Abstract Information :

INTRODUCTIONrnrnMonitoring the wastewater levels in a wastewater network is imperative as it enables utilitiesrnto effectively manage their network to prevent wastewater spills, reduce pollution and improve visibility, performance, and forecasting.rnrnTHE PROBLEM THAT UTILITIES CURRENTLY FACErnrnCurrently, 86% of rivers and inland waterways in England are below the expected water quality standards. Wastewater spills are a major contributor to the contamination of freshwater and marine ecosystems, with further spills into the sea impacting bathing water quality that poses serious health risks and damage to marine ecosystems. Utilities often have poor visibility of their entire network covering some 500,000 km due to expensive remote monitoring equipment only covering crucial points, with responses to wastewater spills typically being a reactionary approach.rnrnBlockages and collapsed sewers often go undetected, whilst control rooms are inundated with high level alarms that are subsequently often turned off during wet weather events due to the impact of rainfall on wastewater network levels.rnrnThese instances result in environmental and reputational damage for utilities, increased expenditure to clean up the damage caused by spills events, as well as being faced with fines issued by regulatory bodies.rnrnREVOLUTIONISING WASTEWATER LEVEL MONITORING WITH IOT AND SMART MACHINE-LEARNING DATA ANALYTICSrnrnThis presentation will explain in detail to the audience how poor wastewater network visibility can be significantly improved when employing a holistic, all-in-one approach for managing Wastewater Levels in a network, through the mass deployment of intelligent, cost-effective IoT sensors across a wastewater network that monitor wastewater levels in real-time. The discussion will demonstrate how high wastewater levels and spillage risks can be pro-actively detected and reported to a secure, scalable data collection and device management platform hosted in the cloud. rnrnThe presentation will further demonstrate how utilities are able to start to intelligently manage their wastewater networks by combining wastewater level data with historic, current and forecast rainfall data, and through the use of smart, machine-learning analytics, start to provide intelligent alarms allowing their control rooms to react to the most important spills.rnrnReal-life examples will be provided to showcase how the implementation of such an innovative, smart approach is allowing for significant reduction in alarms, allowing focus to be placed on those spills that matter.rnrnFurthermore, also being able to provide early warnings of future spills by identifying partial blockages, means that these blockages can be proactively cleared to prevent wastewater spills before they happen.rnrnThe presentation will conclude by highlighting the benefits to the audience of how such a proactive, all-in-one approach will provide ultimate network visibility, performance, and forecasting; early blockage detection, improved sewer, pumping station and treatment works performance, prevent wastewater spills and reduce pollution to protect the natural environment.rn

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ETP ILM Environment Agency RSC Group Water Forum.jpg RSC Group Science Forum.jpg Cogdem WMA Pump Centre SWIG Profilbus CIWEM Future Water Association Gambica WRC LPRA Zero Pollution Network WIPAC British Water Swan UKAS Scottish Environment Protection Agency Environment Protection Agency Natural Resources Wales Profibus