Partners Paige Wireless and SAS Work to Predict and Prevent the Effects of Flooding Using IoT Analytics
Paige Wireless and analytics leader SAS have become partners to solve community-centered challenges like those that affect agriculture, economic development, and smart governments. Using Paige Wireless’ carrier-grade LoRaWAN network, IoT-enabled sensor technology, and SAS’ artificial intelligence (AI) solutions, flood control is the first tough challenge the partners will tackle.
Frequent flooding events can wreak havoc on communities, closing roads, destroying infrastructure, interrupting essential services, and posing a safety risk to all that live, work, and play in affected areas. Flooding concerns continue to grow. Experts predict that by 2030, the number of people affected by flooding will more than double.
“Flooding is a critical concern for government, business, and society globally,” says Jason Mann, SAS Vice President of IoT. “Customers will benefit from new and compelling insights that enhance early alerting systems and enable preventative action and real-time responsiveness. With an AI-powered predictive analytics solution built on SAS Analytics for IoT integrated with the Paige Wireless carrier-grade LoRaWAN network and advanced sensor technology, SAS and Paige Wireless are mitigating this escalating threat to life, property, and commerce.”
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“Paige Wireless joined forces with analytics leader SAS to solve deeply important problems facing communities,” said Julie Bushell, President of Paige Wireless. “We are already seeing results from helping municipalities avoid the devastation of flash flooding, and we’re confident that we will improve lives.”
The partners work with local governments to mitigate flooding risks before they happen. Learn more about the work by downloading the eBook, Making the Unpredictable Predictable. The eBook shares insights and key learnings from working with municipalities. It underscores the importance of working with the right partners and leveraging the right technology tools, to prevent flood damage and predict flood patterns.
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