SAS® IoT to power China’s Wuxi High-Tech Zone

By AIT News Desk On Sep 19, 2018

Partnership builds on SAS’ position as the IoT analytics leader in smart cities arenas

ANALYTICS EXPERIENCE – China’s Wuxi High-Tech Zone recently selected SAS as its strategic Internet of Things (IoT) analytics partner. Wuxi is the latest in a series of IoT smart cities projects that strengthen SAS’ position as a critical technology player in these arenas. The announcement was made at the SAS Analytics Experience conference in San Diego.

SAS selected as strategic IoT analytics partner for China’s Wuxi High-Tech Zone.

“Smart cities are built on strategic layers of complementary technologies – smart electrical grids that help manage energy use; connected vehicles that keep drivers safe; connected traffic lights and public transportation systems that keep traffic on schedule; and connected buildings that help owners manage temperature, air quality and lighting,” said Jason Mann, SAS Vice President of IoT. “The connected devices, citizens and environments generate an enormous volume of diverse data that must be analyzed at the edge to drive accurate, real-time decision making. SAS provides advanced IoT analytics with embedded artificial intelligence (AI) and machine learning (ML) capabilities to help extract value smart cities use to improve quality of life.”

SAS is involved in a variety of IoT smart cities projects:

Boston Public Schools reduced its fleet by 50 buses and shaved a million miles off the number of annual miles driven after using SAS to analyze student, school, neighborhood and bus data.
GE Transportation uses SAS to decipher locomotive IoT data and uncover operational insights from use patterns that keep trains running on schedule.
The Town of Cary, NC, makes it easier to find and fix water loss issues. With help from SAS, the town of 162,000 residents has gained a big-picture view of water use critical to planning future water plant expansions and promoting targeted conservation efforts.
The Wake County Revenue Department in North Carolina uses SAS AI analytics along with ML algorithms to forecast property values and extend the reach of overburdened tax appraisers.

Mann said SAS and Wuxi will establish an IoT Innovation Center and jointly promote big data analytics and IoT technologies to the pharmaceutical, manufacturing, utilities and transportation industries. He will be a speaker at the AI Forum of the 2018 World Internet of Things Exposition in Wuxi on Sept. 17. Representatives from more than 500 companies are expected to attend this showcase of the latest advances in big data, IoT and AI.

Among the many joint initiatives, Wuxi will use SAS^® Analytics for IoT – composed of SAS^® Visual Data Mining and Machine Learning, SAS^® Visual Analytics and SAS^® Event Stream Processing – to analyze high-velocity IoT devices, networks, applications and data in motion so it can take meaningful, immediate action. SAS Event Stream Processing is scalable, embeddable and distributable, and it strengthens SAS’ position in the growing edge analytics market. The Forrester Wave™: Streaming Analytics, Q3 2017 report cited SAS Event Stream Processing as a Leader in this space.

Smart cities = huge potential

Industry analyst firm IDC predicts that by 2020 the IoT analytics market will reach more than US$23 billion, and there will be 20.4 billion IoT connected devices generating data. Research firm Frost & Sullivan anticipates smart cities will create more than $2 trillion in market value by 2025, and the Asia-Pacific region will be the fastest-growing region for smart cities.

With its deep IoT experience, SAS helps customers meet the challenges of IoT growth and adoption. IoT-related revenue growth in 2017 led to SAS establishing a global IoT division in January 2018. The SAS IoT data platform supports the complete analytics life cycle – from data ingestion to analysis to model deployment – and reveals meaningful insights from IoT data regardless of its quantity, type or speed. Customers can make better decisions and act quickly using the real-time insights that arise from data visualization, machine learning and streaming analytics.