From Ad Hoc Maintenance to Predictive Analytics: Revolutionizing IoT Water Monitoring with ThingsLog and Advanced Forecasting Algorithms
In the world of IoT water monitoring, the shift from reactive, ad hoc maintenance to proactive, predictive analytics is transforming how we manage water resources. With the integration of advanced technologies like deep learning algorithms, time-series forecasting models, and zero-shot forecasting powered by large language models (LLMs), platforms like ThingsLog are leading the charge in […]
Datasets to Train Generative AI for Non-Revenue Water Management
Non-Revenue Water (NRW)—water lost before it reaches consumers due to leaks, theft, or metering inaccuracies—is a significant challenge for water utilities worldwide. Generative AI models, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), have shown immense potential in addressing NRW challenges by simulating water distribution networks, predicting leaks, and optimizing infrastructure. However, training […]
Harnessing Generative AI for Non-Revenue Water Management: A Game-Changer for Water Utilities
Water utilities worldwide face the persistent challenge of Non-Revenue Water (NRW)—water that is lost before it reaches consumers due to leaks, theft, or metering inaccuracies. Reducing NRW is critical for ensuring sustainable water management, conserving resources, and improving operational efficiency. Recent advancements in generative artificial intelligence (AI), particularly its ability to work with time-series datasets, […]
