Workshop: Solve AI and ML Edge Data Processing and Data Management Design

Description

Mission-critical applications face many edge data management challenges, including performance, scalability, security, and data maintenance cost. The right development tools empower devices to meet these challenges and enable IoT nodes to monitor, process and manage a large volume of time series data quickly and efficiently, in real time.

Database capabilities for pre-trained Artificial Intelligence algorithms and standard Machine Learning development projects require special capabilities to optimize data digestion and distribution. Data processing and data management are one of the most critical components in building such embedded systems and devices to monitor the data in real time. By managing and storing data at its source location, manufactures benefit from security and minimizing total cost of ownership (TCO) by enabling devices to deliver fast local analytics, save bandwidth, and obviate the need for off premises data storage maintenance costs.

With our half-day online workshop, you will learn how, with ITTIA database and a device, you can easily build IoT data driven framework to monitor, manage and distribute a large volume of real time sensor data at the edge. You will experience how your device application processors can accomplish low latency and high throughput.

You will learn the device capability for taking on a major IoT-related computing responsibility in providing immediate results when monitoring raw data locally captured and analyzed.

Prerequisites

• Access to internet and required equipment to attend the session online
• Basic familiarity with fundamental database, C and C++ programming languages
• Familiarity with embedded and devices software development and constrains

Objectives

Attendees will be introduced to embedded systems and edge IoT device data management and processing challenges and learn important options for countering them.

• Silently embedding database to monitor, process and manage device data
• Ingest data from multiple time series sources onto flash media at high rate
• Minimize RAM, code, and storage media footprint
• Query from individual series and export from all series at once

Training Topics

Unlock the power of real time data by monitoring and capturing a variety of time series sensor data from the equipment onto edge devices. Build efficient embedded systems to increase productivity, improve quality and device predictability.

First Session: Live Demonstrations

Experience both data processing and data management on a device:

• Process live IoT sensor data in real time: combine, aggregate, and downsample on demand
• Simulate and store a full day of data originating from multiple sensors
• Query individual sensors to graph and analyze over any time range
• Export stored data, ordered by time, in various formats: CSV, JSON, XML, Protobuf2
• Benchmark report: ingestion rate, query read latency, export throughput

Second Session: How to Begin Real Time Stream Data Processing

Explore essential skills to monitor and process IoT data in a local edge database:

• Design and initialize a schema
• Generate IoT sensor records
• Query real time values
• Throughput and latency

Enrollment

The cost for this one-day training seminar is US$299 per developer unless you have a promotion code.