IoT Archives - Page 320 of 453 - SmartCitiesElectronics.com

ToF sensor module offers detects moving objects, says Omron

Fri, Oct 09, 2020

The 3D precision time of flight (ToF) ranging sensor module delivers positioning, autonomous-guidance and proximity sensing for a wide range of applications. Gabriele Fulco, European product marketing manager of sensors at Omron described the B5L-A2S-U01-010 as a mechanical eye that is capable of accurately detecting the surrounding environment. It is expected to contribute to the more widespread use of autonomous robots as well as the automation of various other machinery and equipment.

The B5L sensor module can be fitted to moving objects such as autonomous mobile robots, to provide real-time contextual information such as guidance, collision avoidance, and cliff detection. Alternatively, located in a fixed position, the sensor can accurately detect moving objects in the field of view, making it equally suitable for use in automated packaging equipment, security systems, intruder detection, and patient-monitoring and care for the elderly systems.

The Omron B5L-A2S-U01-010 operates on the proven ToF principle, calculating distances to objects in real time by measuring the round-trip time for near-infra red radiation from the module’s emitter to be reflected from objects in the field of view and returned to the receiver. The B5L’s optical design technology for the stable measurement of three-dimensional distance information operates across a wide area even in sub-optimal conditions, such as under sunlight, says Omron. Running at up to 20 frames per second, its specifications are optimised for long periods of continuous operation to allow it to be used as an embedded sensor in various instruments.

The 103 x 43mm module is fitted with a 24V DC power connector and Micro-USB communication port, offering easy integration and flexibility for embedded systems designers. The 940nm near-infra red emitter and 240 x 320 pixel receiving array, gives ranging information for the entire field of view and measures the absolute distance to objects from 0.5m to 4m. The module offers ±2 per cent precision (at a detection distance of 2m). Built-in temperature compensation simplifies its integration into autonomous robots and other equipment as it eliminates the need for the design of separate compensation processing for different environments.

The wide viewing angle and 0 to 50 degrees C operating temperature range, means that the B5L-A2S-U01-010 can be used in various indoor applications.

The B5L-A2S-U01-010 is in production now and available directly from Omron Electronic Components Europe or through its network of European distributors.

http://components.omron.eu

> Read More

Neural network accelerator chip enables IoT AI in battery-powered devices

Thu, Oct 08, 2020

To reduce energy consumption and latency by a factor of over 100 to enable complex embedded inference decisions at the IoT edge, Maxim Integrated has developed the MAX78000 low power neural network accelerated microcontroller.

It moves AI to the edge without performance compromises in battery-powered internet of things (IoT) devices, says the company. It is able to execute AI inferences at less than 1/100th the energy of software solutions to dramatically improve the run-time for battery-powered AI applications. It also enables new, complex AI use cases.

The MAX78000 executes inferences 100x faster than software running on low power microcontrollers and at a fraction of the cost of FPGAs or GPUs, continues Maxim.

Rather than gathering data from sensors, cameras and microphones, sending that data to the cloud to execute an inference, then sending an answer back to the edge, which is challenging due to poor latency and energy performance. Using low power microcontrollers can be used to implement simple neural networks but latency suffers and only simple tasks can be run at the edge. By integrating a dedicated neural network accelerator with a pair of microcontroller cores, the MAX78000 overcomes these limitations, enabling machines to see and hear complex patterns with local, low-power AI processing that executes in real-time.

Applications such as machine vision, audio and facial recognition can be made more efficient as the MAX78000 can execute inferences at less than 1/100th the energy required by a microcontroller. The MAX78000’s specialised hardware is designed to minimise the energy consumption and latency of convolutional neural networks (CNNs). Hardware runs with minimal intervention from any microcontroller core, making operation extremely streamlined. Energy and time are only used for the mathematical operations that implement a CNN. To get data from the external world into the CNN engine efficiently, customers can use one of the two integrated microcontroller cores: the low power Arm Cortex-M4 core, or the even lower power RISC-V core.

The MAX78000EVKIT# includes audio and camera inputs, and out-of-the-box running demos for large vocabulary keyword spotting and facial recognition. Complete documentation helps engineers train networks for the MAX78000 in the tools they are used to using, either TensorFlow or PyTorch.

The MAX78000 is available from authorised distributors. The MAX78000EVKIT# evaluation kit is also available now.

http://www.maximintegrated.com

> Read More

Software development kit by XMOS addresses AI for the IOT

Thu, Oct 08, 2020

Tools and resources to accelerate the development of devices that can think for themselves in an intelligent IoT have been collated by XMOS. The software development kit (SDK) for the artificial intelligence of things (AIoT) includes TensorFlowLite for Microcontroller development tools. The SDK is designed to harness xcore.ai and make it easier for engineers to develop connected products that can sense, think, decide and act.

The kit has standardised tools and resources developers can used to create devices that absorb contextual data from their environment, infer meaning from that data, and translate the results into action.

AIoT tools include scripts, tools and libraries to convert TensorFlowLite for Microcontroller models into a format that targets accelerated operations on the xcore.ai platform. There are also libraries to support FreeRTOS operation on xcore.ai, for a standard industry programming environment.

Examples show a variety of operations based on bare-metal and FreeRTOS operation, including smart microphone sensing. There is also documentation (getting started guides, example builds and execution walkthroughs) and access to XMOS’ open-source libraries of interfaces and signal processing algorithms.

The tools are designed to enable developers to rapidly deploy custom or off-the-shelf AI models using a standard framework alongside all of the control, communications, signal and I/O processing required to create a complete and secure application, says XMOS.

“Our AIoT SDK enables developers to create intelligent endpoint-AI solutions for a huge variety of applications,” said Mark Lippett, CEO of XMOS. “The flexibility of the xcore.ai architecture enables our customers to create truly differentiated solutions using standard embedded software techniques like TensorFlowLite for MCU in a fraction of the time required using traditional hardware approaches.”

Early access to the XMOS AIoT SDK will be available on the GitHub open source platform, designed to be used in conjunction with the xcore.ai Explorer Kit, which is available on limited release via xmos.ai.

Future releases will include other xcore.ai hardware platforms, targeting specific use case applications. An example is a smart home platform. This small form factor reference design with additional Wi-Fi capability is designed to demonstrate the capabilities of voice at the edge of networks. It is due to be released in early 2021.

http://www.xmos.ai

> Read More

DAC includes non-volatile memory to simplify handheld designs, says Microchip

Wed, Oct 07, 2020

Microchip claims to have overcome the problems of implementing multi-channel system control or signal outputs using DACs in portable and handheld industrial, communications, consumer or medical systems. To overcome the need for significant processor overhead for device configuration during power-up, the MCP47/48FxBx8 family of octal 12-bit DACs include non volatile memory and an integrated voltage reference (Vref) source so they can be pre-configured for safe and efficient power-up without relying on the system processor.

“Handhelds and other portable systems are expected to deliver more capabilities in smaller, simpler designs,” said Bryan J. Liddiard, vice president of Microchip’s mixed-signal and linear business unit. “We help achieve this goal with the first DACs that eliminate processor overhead during power-up and provide the channel density, low power consumption and integrated features that today’s compact systems need so they can operate over longer periods using smaller, lighter batteries,” he added.

The inclusion of non-volatile memory means that the MCP47/48FxBx8 DACs can store user-customised configuration data even when powered down. At power-up, all eight channels are then configured to the pre-defined state without burdening the system processor with this overhead.

Integrating a Vref source into the DACs reduces overall system size and complexity while providing the control to meet critical timing for safely driving all power outputs. The devices also have both SPI and I2C serial interfaces for a choice of device communication.

Operating voltage range is 1.8V to 5.5V and the DACs’ low minimum operating voltage and its power efficiency are claimed to improve thermal performance and reliability. The DACs also provide power-on/brown-out reset protection and what is claimed to be one of the industry’s fastest settling times at five micro seconds. They also operate in the extended temperature range (i.e. -40 to +125 degrees C) for industrial and automotive applications.

The MCP47/48FxBx8 family of DACs is available for volume orders. The family includes 8-, 10- and 12-bit resolution devices in a 20-lead VQFN 5.0 x 5.0mm package and a 20-lead TSSOP package.

http://www.microchip.com

> Read More

ToF sensor module offers detects moving objects, says Omron

Neural network accelerator chip enables IoT AI in battery-powered devices

Software development kit by XMOS addresses AI for the IOT

DAC includes non-volatile memory to simplify handheld designs, says Microchip

About Smart Cities