HomeLatest ProductsSTMicroelectronics’ “Intelligent Sensor Processing Unit” Integrates Brains into Sensors to Launch Onlife...

    STMicroelectronics’ “Intelligent Sensor Processing Unit” Integrates Brains into Sensors to Launch Onlife Era

    STMicroelectronics, today announced the launch of the Intelligent Sensor Processing Unit (ISPU) that combines a Digital Signal Processor (DSP) suited to run AI algorithms and MEMS sensor on the same silicon.

    In addition to reducing size over system-in-package devices and cutting power by up to 80%, merging sensor and AI puts electronic decision-making in the application Edge. Here, it facilitates the Onlife Era where innovative products enabled by smart sensors are able to sense, process, and take actions, bringing the fusion of technology and the physical world.

    The Onlife Era acknowledges living with continuous assistance from connected technologies, enjoying natural, transparent interactions, and seamless transitions, with no discernible distinction between online and offline. With the ISPU, ST is enabling this era by helping to migrate intelligent processing into sensors that support the fabric of life: no longer at the Edge but in the Edge.

    ST’s ISPU provides substantial benefits in the four Ps: power consumption, packaging, performance, and price. The proprietary ultra-low-power DSP can be programmed in C, familiar to many engineers. It also allows quantized AI sensors to support full- to single-bit-precision neural networks. This ensures superior accuracy and efficiency in tasks such as activity recognition and anomaly detection by analyzing inertial data.

    While technically challenging, integrating ST’s sensors on the same piece of silicon with our ISPU does improve sensor-based systems from an online experience to an Onlife one. It advances the sensor’s features to speed decision-making by reducing data transfers, enhancing privacy by keeping data local, while reducing size and power consumption, which cuts costs,” said Andrea Onetti, Executive Vice President, MEMS Sub-Group, STMicroelectronics. “Moreover, the ISPU is easily programmable with commercial AI models and can ultimately operate with all of the leading AI tools.”

    Technical Notes for Editors:
    ST’s proprietary, C-language-programmable DSP is an enhanced 32-bit Reduced Instruction Set Computing (RISC) machine. It is extensible (in the chip-design phase) for dedicated instructions and hardware components. The processor offers a full-precision floating-point unit, uses a fast four-stage pipeline, operates from 16-bit variable-length instructions, and includes a single-cycle 16-bit multiplier. Interrupt response is a spritely four cycles. ST’s sensors with ISPUs will be packaged in standard 3mm x 2.5mm x 0.83mm packages and will be pin-compatible with their (ST) predecessors, allowing quick upgrades.

    Combining the sensor and ISPU is also a big power saver; ST’s calculations show a 5-6x saving over System-in-Package approaches in sensor-fusion applications. They also show a 2-3x saving in RUN mode.

    For more information please go to www.st.com/ispu

    ELE Times News
    ELE Times Newshttps://www.eletimes.ai/
    ELE Times provides extensive global coverage of Electronics, Technology, and the Market. In addition to providing in-depth articles, ELE Times attracts the industry’s largest, qualified, and highly engaged audiences, who appreciate our timely, relevant content and popular formats. ELE Times helps you build experience, drive traffic, communicate your contributions to the right audience, generate leads, and market your products favorably.

    Related News

    Must Read

    Reinforcement Learning Definition, Types, Examples and Applications

    Reinforcement Learning (RL), unlike other machine learning (ML) paradigms,...

    Infineon drives industry transition to Post-Quantum Cryptography on PSOC Control microcontrollers

    Infineon Technologies AG announced that its microcontrollers (MCUs) in...

    Decision Tree Learning Definition, Types, Examples and Applications

    Decision Tree Learning is a type of supervised machine...

    Renesas Introduces Ultra-Low-Power RL78/L23 MCUs for Next-Generation Smart Home Appliances

    Ultra-low-power RL78/L23 MCUs with segment LCD displays & capacitive...

    STMicroelectronics Appoints MD India

    Anand Kumar is the Managing Director of STMicroelectronics (ST),...

    Top 10 Federated Learning Applications and Use Cases

    Nowadays, individuals own an increasing number of devices—such as...

    Top 10 Federated Learning Companies in India

    Federated learning is transforming AI’s potential in India by...