A Complete Artificial Intelligence (AI) System Platform with
Sensor processing
eFPGA for feature extraction
Neurons for AI computing
Data analytics SW for data training and model/classifier building
Scaling across bigger AI systems with thousands of endpoint devices
No need for in-house expertise of data analytics, DSP processing, app coding
Delivers an AI module solution that can be deployed at the endpoint devices with different connectivity, sensor
Addressing the Challenges of Endpoint Applications
- Companies developing endpoint devices often lack the resources to work effectively with the complexities of cloud-based AI
- Endpoint applications often benefit from local AI resources that can react quickly, lower endpoint power consumption and lower life-cycle costs
- Endpoint design teams often lack the Data Science and Firmware Engineering resources needed to develop AI models
- The diversity and uniqueness of endpoint use cases drive the need to develop application specific algorithms and models
- Once deployed, endpoint companies must have a plan to manage the distributed endpoints, leverage the information they collect and often update AI models remotely
QuickAI Platform
QuickLogic– The EOS™ S3 voice and sensor processing platform make it the ideal host SoC for the NM500. It can implement the proprietary interface for the NM500, sample the IoT sensor data, and extract features using its embedded FPGA technology.
SensiML – The analytics toolkit quickly and easily trains the data, builds the model and classifier and programs the EOS S3 for endpoint AI.
Nepes – The NM500 implements the NeuroMem technology in an energy efficient, small form factor component. It can be trained in the field to recognize patterns in real time, and multiple devices can be chained to provide any number of neurons. The Knowledge Studio software tool can be used to configure and train the neurons in the NM500 device.
Example Applications
Features: Vision Inspection for Fruit/Vegetable Harvesting
* Available Q2 2019
Features:
- Identify ripe fruit/ vegetable from unripe fruit/vegetable
- QuickAI HDK Platform (with camera interface) can be used for evaluation and/or deployment
- HDK using UART interface to drive servo motors
FPGA Features:
- Sensor Data -> Feature Extraction -> Vector
- Interface to neurons and camera
Industrial Predictive Maintenance
- Unique model doesn’t scale across similar motor differences in mounting or loading
- Endpoint AI decreases system bandwidth, latency, power
Algorithm Development: SensiML Toolkit for Time Series
- Data collection, segmenting, labeling
- Sensor input: motion, audio, pressure, temp/humidity, other time series data
- Feature extraction
- Model building
FPGA Features
- Sensor Data Creation → Feature Extraction → Feature Vector
- Hardware accelerator (FFT & MFCC)
- NM500 hard neuron interface
FFE Enabled Features
- Event trigger (segmentation)
- Feature extraction for simpler features
- Ultra-low power AON function
Structural Health Monitoring
- Damage detection
- Structural Integrity reporting
Algorithm Development: SensiML Toolkit for Time Series
- Data collection, segmenting, labeling
- Sensor input: motion, audio
- Feature extraction
- Model building
FPGA Features
- Sensor Data Creation → Feature Extraction → Feature Vector
- Hardware accelerator (FFT)
- NM500 hard neuron Interface
FFE Enabled Features
- Event trigger (segmentation)
- Feature extraction for simpler features
- Vibration (high precision accel) analysis at 200Hz ODR
Merced Hardware Development Kit (HDK)
The Merced HDK is an evaluation platform for QuickLogic’s EOS S3AI SoC. The HDK comes with time-series (continuous) sensors, including:
- Accelerometer/gyroscope/magnetometer motion sensors
- Two digital microphones (PDMs)
The Merced HDK can store data locally using a μSD card or transmit sensor data via a built in BLE module.
Ready to Use - Out of the Box
The Merced HDK is an Arduino form-factor compatible module. This makes it an ideal hardware platform to expand features without developing new hardware. The Merced HDK includes a demo application that makes it ready to use out of the box. The device comes with a boot-from-flash feature to enable users to evaluate QuickAI™ applications. It also links directly with the SensiML Data Analytics Toolkit in order to collect data, develop AI models, algorithms and new classifiers. Updating the Merced HDK is possible via an on-board USB-2-UART connection. This enables the creation of demos and prototypes without any additional development time or resources.
Ordering Information
To order, refer to part number QAI-EVALKIT-AA-1.0 and contact sales.
