Machine learning and data analytics have already changed our lives and they are now changing the way we do business. The latest tools allow artificial intelligence and machine learning techniques to highlight the root causes of issues both as they arise but also in advance of problems that then lead onto “noisy” alarm flooding events. AI-based root cause detection solutions interpret thousands of sensor feeds and alarms to establish the likely root causes. Our white paper goes on to describe how this not only reduces “false alarms” significantly, but also focusses attention and improves resource allocation.
Our third white paper in the current series describes how Situational Awareness from HAL24K-Water brings together multiple complex systems within a centralised, secure, cloud-based platform that is built to respond to diverse needs with data informed insight.
For water company personnel and management, Situational Awareness from HAL24K Water provides an integrated view of organisational information, creating data empowered users with enhanced skills and more efficiently managed workloads, across the company. This is achieved through digital automation, data optimisation and a live view of risks which allows the utility to move from reactive responses to proactive and truly strategic management - with all associated performance and cost benefits.
For the water industry, the ability of AI solutions to learn and problem solve at an unprecedented pace will be critical to help them meet its major challenges - water scarcity and improving resilience in an era of ageing infrastructure, climate change, severe weather events and over-population. Water companies must deliver this whilst maintaining exacting environmental and public health standards.
Our white paper describes how HAL24K-Water solutions are able to detect inefficient pumps, sensors and meters making expensive emergency maintenance procedures much less frequent. Water companies using our AI in their smart systems can optimise performance levels and significantly improve their operating conditions.
Attaching sensors to thousands of kilometres of pipeline on a “per Km” or “just in case” basis may not be the most sensible approach. Especially if extraction and relocation of those assets is subsequently difficult. At HAL24K-Water we are using the latest AI and machine learning techniques to characterise the key factors that identify where sensors are most needed across an entire network.
For water companies to gain value from asset data and the latest advancements in Artificial Intelligence it is paramount that assets are labelled in a structured and reliable fashion. But…. asset labelling across all the utility industries is widely held to be inconsistent and sometimes incorrect. This quick read from HAL24K-Water describes how complex data is rapidly cleansed so that full can be derived and acted upon.
Our ready to integrate solution removes the pains of recruiting data scientists, laborious R&D, and the myriad problems that come with big-data implementations. Instead we provide ready to operate operational tools operations teams with easy-to-deploy, easy-to-use, data-driven applications for water companies.
In this Quick Read we describe how HAL24K WATER's Situational Awareness platform is built on the DIMENSION™ AI/ML infrastructure and be easily used by your organisation using open and common AI tools such as Plotly, Python, scikit-learn, NumPy and Jupyter.
Operational systems are too often focussed on detecting significant failures. However, enriching large-scale telemetry with AI systems to quantify the underlying risks being carried by operating processes can bring genuine value. Our quick read on Risk management and AI proposes that it is time to let your water company data do more than just ring alarm bells.