IoT Innovators: SAS AIoT Reimagined with Custom Analysis Framework

bkooman — Fri, 12 Sep 2025 18:22:17 GMT

In the age of connected devices and industrial intelligence, organizations are generating massive volumes of sensor data—but turning that data into actionable insights remains a challenge. That’s where Analytics for IoT (AIoT) and the Custom Analysis Framework (CAF) come in.

What Is AIoT?

AIoT is a solution framework that helps organizations transform raw sensor data into meaningful insights. Built on SAS Viya, it supports:

High-volume data ingestion and management for time-series and sensor data
Streaming analytics for real-time event detection and scoring
Machine learning models to predict failures and optimize quality
Visualization dashboards for engineers and operators
Edge-to-cloud deployment for scalable industrial operations

AIoT bridges the gap between operational data and business outcomes—enabling predictive maintenance, anomaly detection, and efficiency improvements across industries like manufacturing, energy, and transportation.

What Is CAF and Why Does It Matter?

The Custom Analysis Framework (CAF) was developed to extend the flexibility of AIoT. Since no single product can address every use case out of the box, CAF empowers users to tailor analytics to their unique environments—without waiting for new product features or custom development.

CAF is a low-code framework that:

Simplifies the creation and reuse of analytics workflows
Connects data science with operational use cases
Reduces the need for custom coding
Accelerates deployment across assets and sites
Embeds domain expertise into reusable workflows

Key Benefits of CAF

Organizations using CAF gain:

Faster time-to-value by deploying analytics quickly
Amplified expertise through reusable workflows
Customization and flexibility with support for SAS, Python, and R
Scalability across plants and processes
Improved collaboration between analytics teams and frontline users

Who Uses CAF and How?

CAF is designed for:

Heavy industries like manufacturing and utilities
Data scientists and domain experts who build advanced analytics
Engineers and operators who apply workflows without coding

Use cases include:

Anomaly detection using SVDD
Vibration analysis via spectrograms
Operational intelligence for uptime and quality improvements

The Future of AIoT and CAF

SAS is enhancing CAF with AI-driven workflow creation, including:

Intelligent recommendations and templates
Guided assistance for non-technical users
AI co-pilots to streamline design and deployment

These innovations will further democratize analytics, empowering domain experts to build and deploy workflows independently—shortening time-to-value and expanding impact across the enterprise.

If you would like to learn more, please contact David Frede <david.frede@sas.com> or Priya Sharma <priya.sharma@sas.com>.