BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
thelittleshort
Top Bloke
BrainChip on LinkedIn: BrainChip University AI Accelerator
BrainChip Empowers Next Generation of Technology Innovators with Launch of the University AI Accelerator Program - Learn more here: https://lnkd.in/gsqM6j3t
cosors
👀
Actually an interesting very tasty recipe: Neuromophic silicon with graphite, some graphene and as sauce binder SiOx as flash killer and lithium as topping. I'm going to bed and you might heat up the stock market. l read you tomorrow!I don't wish you any success with it.) But I'm actually itching to buy too. It's like a fire that I have to nurture. If I put nothing after it can not blaze. Even if I had actually filled my pot and when lid down I see almost only BRN with graphene. But I'm also a collector. I can never have enough. Since November I have never felt such peace with a stock. Yak has also contributed to this. It's strange but that's the way it is for me. Would be nice if he would give updates again. On the one hand the collective insights into the technology and on the other hand the sober look at the mechanisms of the big game. But patience with me. I am currently learning in the bars here very much important for my life. How I have survived so far without Vegemite is a mystery to me
Sorry
forgot Vegemite
Fullmoonfever
Top 20
Just saw the article as well.
BrainChip on LinkedIn: BrainChip University AI Accelerator
BrainChip Empowers Next Generation of Technology Innovators with Launch of the University AI Accelerator Program - Learn more here: https://lnkd.in/gsqM6j3twww.linkedin.com
Back to Newsroom
BrainChip Empowers Next Generation of Technology Innovators with Launch of the University AI Accelerator Program
Tuesday, August 16, 2022 5:30 PM
Brainchip Holdings Limited/ADR
Home
Unlock the power of AI with BrainChip. Enhance data processing, Edge apps and neural networks at the speed of tomorrow. Explore now!
brainchip.com
Share this Article
Topic:
Product Announcements
LAGUNA HILLS, CA / ACCESSWIRE / August 16, 2022 / BrainChip Holdings Ltd (ASX:BRN) (OTCQX:BRCHF) (ADR:BCHPY), the world's first commercial producer of neuromorphic AI IP, is bringing its neuromorphic technology into higher education institutions via the BrainChip University AI Accelerator Program, which shares technical knowledge, promotes leading-edge discoveries and positions students to be next-generation technology innovators.
BrainChip's University AI Accelerator Program provides hardware, training, and guidance to students at higher education institutions with existing AI engineering programs. BrainChip's products can be leveraged by students to support projects in any number of novel use cases or to demonstrate AI enablement. Students participating in the program will have access to real-world, event-based technologies offering unparalleled performance and efficiency to advance their learning through graduation and beyond.
The Program successfully completed a pilot session at Carnegie Mellon University this past spring semester and will be officially launching with Arizona State University in September. There are five universities and institutes of technology expected to participate in the program during its inaugural academic year. Each program session will include a demonstration and education of a working environment for BrainChip's AKD1000 on a Linux-based system, combining lecture-based teaching methods with hands-on experiential exploration.
"We have incorporated experimentation with BrainChip's Akida development boards in our new graduate-level course, "Neuromorphic Computer Architecture and Processor Design" at Carnegie Mellon University during the Spring 2022 semester," said John Paul Shen, Professor, Electrical and Computer Engineering Department at Carnegie Mellon. "Our students had a great experience in using the Akida development environment and analyzing results from the Akida hardware. We look forward to running and expanding this program in 2023."
BrainChip's first-to-market neuromorphic processor, Akida, mimics the human brain to analyze only essential sensor inputs at the point of acquisition, processing data with unparalleled efficiency, precision, and economy of energy. Keeping AI/ML local to the chip, independent of the cloud, also dramatically reduces latency.
"Universities are looking for the best way to differentiate their curriculum with real-world and hands-on leading-edge technologies," said Sean Hehir, BrainChip's CEO. "By partnering with BrainChip's AI Accelerator Program, universities are able to ensure that students have the tools and resources needed to encourage development of cutting-edge technologies that will continue to usher in an era of essential AI solutions."
Institutions of higher education interested in how they can become members of BrainChip's University AI Accelerator Program can find more details by emailing Sales@brainchip.com.
chapman89
Founding Member
Very interesting.
NASA's Jet Propulsion Laboratory has selected Microchip Technology Inc. to develop a high-performance spaceflight computing processor that will support future space missions.
Credits: NASA
NASA’s Jet Propulsion Laboratory in Southern California has selected Microchip Technology Inc. of Chandler, Arizona, to develop a High-Performance Spaceflight Computing (HPSC) processor that will provide at least 100 times the computational capacity of current spaceflight computers. This key capability would advance all types of future space missions, from planetary exploration to lunar and Mars surface missions.
“This cutting-edge spaceflight processor will have a tremendous impact on our future space missions and even technologies here on Earth,” said Niki Werkheiser, director of technology maturation within the Space Technology Mission Directorate at NASA Headquarters in Washington. “This effort will amplify existing spacecraft capabilities and enable new ones and could ultimately be used by virtually every future space mission, all benefiting from more capable flight computing.”
Microchip will architect, design, and deliver the HPSC processor over three years, with the goal of employing the processor on future lunar and planetary exploration missions. Microchip’s processor architecture will significantly improve the overall computing efficiency for these missions by enabling computing power to be scalable, based on mission needs. The design also will be more reliable and have a higher fault tolerance. The processor will enable spacecraft computers to perform calculations up to 100 times faster than today’s state-of-the-art space computers. As part of NASA's ongoing commercial partnership efforts, the work will take place under a $50 million firm-fixed-price contract, with Microchip contributing significant research and development costs to complete the project.
"We are pleased that NASA selected Microchip as its partner to develop the next-generation space-qualified compute processor platform.” said Babak Samimi, corporate vice president for Microchip’s Communications business unit. “We are making a joint investment with NASA on a new trusted and transformative compute platform. It will deliver comprehensive Ethernet networking, advanced artificial intelligence/machine learning processing and connectivity support while offering unprecedented performance gain, fault-tolerance, and security architecture at low power consumption. We will foster an industry wide ecosystem of single board computer partners anchored on the HPSC processor and Microchip’s complementary space-qualified total system solutions to benefit a new generation of mission-critical edge compute designs optimized for size, weight, and power.”
Current space-qualified computing technology is designed to address the most computationally-intensive part of a mission – a practice that leads to overdesigning and inefficient use of computing power. For example, a Mars surface mission demands high-speed data movement and intense calculation during the planetary landing sequence. However, routine mobility and science operations require fewer calculations and tasks per second. Microchip’s new processor architecture offers the flexibility for the processing power to ebb and flow depending on current operational requirements. Certain processing functions can also be turned off when not in use, reducing power consumption. This capability will save a large amount of energy and improve overall computing efficiency for space missions.
“Our current spaceflight computers were developed almost 30 years ago,” said Wesley Powell, NASA’s principal technologist for advanced avionics. “While they have served past missions well, future NASA missions demand significantly increased onboard computing capabilities and reliability. The new computing processor will provide the advances required in performance, fault tolerance, and flexibility to meet these future mission needs.”
Microchip’s HPSC processor may be useful to other government agencies and applicable to other types of future space mission to explore our solar system and beyond, from Earth science operations to Mars exploration and human lunar missions. The processor could potentially be used for commercial systems on Earth that require similar mission critical edge computing needs as space missions and are able to safely continue operations if one component of the system fails. These potential applications include industrial automation, edge computing, time-sensitive ethernet data transmission, artificial intelligence, and even Internet of Things gateways, which bridge various communication technologies.
In 2021, NASA solicited proposals for a trade study for an advanced radiation-hardened computing chip with the intention of selecting one vendor for development. This contract is part of NASA’s High-Performance Space Computingproject. HPSC is led by the agency’s Space Technology Mission Directorate’s Game Changing Development program with support from the Science Mission Directorate. The project is led by JPL, a division of Caltech.
NASA Awards Next-Generation Spaceflight Computing Processor Contract
NASA's Jet Propulsion Laboratory has selected Microchip Technology Inc. to develop a high-performance spaceflight computing processor that will support future space missions.
Credits: NASA
NASA’s Jet Propulsion Laboratory in Southern California has selected Microchip Technology Inc. of Chandler, Arizona, to develop a High-Performance Spaceflight Computing (HPSC) processor that will provide at least 100 times the computational capacity of current spaceflight computers. This key capability would advance all types of future space missions, from planetary exploration to lunar and Mars surface missions.
“This cutting-edge spaceflight processor will have a tremendous impact on our future space missions and even technologies here on Earth,” said Niki Werkheiser, director of technology maturation within the Space Technology Mission Directorate at NASA Headquarters in Washington. “This effort will amplify existing spacecraft capabilities and enable new ones and could ultimately be used by virtually every future space mission, all benefiting from more capable flight computing.”
Microchip will architect, design, and deliver the HPSC processor over three years, with the goal of employing the processor on future lunar and planetary exploration missions. Microchip’s processor architecture will significantly improve the overall computing efficiency for these missions by enabling computing power to be scalable, based on mission needs. The design also will be more reliable and have a higher fault tolerance. The processor will enable spacecraft computers to perform calculations up to 100 times faster than today’s state-of-the-art space computers. As part of NASA's ongoing commercial partnership efforts, the work will take place under a $50 million firm-fixed-price contract, with Microchip contributing significant research and development costs to complete the project.
"We are pleased that NASA selected Microchip as its partner to develop the next-generation space-qualified compute processor platform.” said Babak Samimi, corporate vice president for Microchip’s Communications business unit. “We are making a joint investment with NASA on a new trusted and transformative compute platform. It will deliver comprehensive Ethernet networking, advanced artificial intelligence/machine learning processing and connectivity support while offering unprecedented performance gain, fault-tolerance, and security architecture at low power consumption. We will foster an industry wide ecosystem of single board computer partners anchored on the HPSC processor and Microchip’s complementary space-qualified total system solutions to benefit a new generation of mission-critical edge compute designs optimized for size, weight, and power.”
Current space-qualified computing technology is designed to address the most computationally-intensive part of a mission – a practice that leads to overdesigning and inefficient use of computing power. For example, a Mars surface mission demands high-speed data movement and intense calculation during the planetary landing sequence. However, routine mobility and science operations require fewer calculations and tasks per second. Microchip’s new processor architecture offers the flexibility for the processing power to ebb and flow depending on current operational requirements. Certain processing functions can also be turned off when not in use, reducing power consumption. This capability will save a large amount of energy and improve overall computing efficiency for space missions.
“Our current spaceflight computers were developed almost 30 years ago,” said Wesley Powell, NASA’s principal technologist for advanced avionics. “While they have served past missions well, future NASA missions demand significantly increased onboard computing capabilities and reliability. The new computing processor will provide the advances required in performance, fault tolerance, and flexibility to meet these future mission needs.”
Microchip’s HPSC processor may be useful to other government agencies and applicable to other types of future space mission to explore our solar system and beyond, from Earth science operations to Mars exploration and human lunar missions. The processor could potentially be used for commercial systems on Earth that require similar mission critical edge computing needs as space missions and are able to safely continue operations if one component of the system fails. These potential applications include industrial automation, edge computing, time-sensitive ethernet data transmission, artificial intelligence, and even Internet of Things gateways, which bridge various communication technologies.
In 2021, NASA solicited proposals for a trade study for an advanced radiation-hardened computing chip with the intention of selecting one vendor for development. This contract is part of NASA’s High-Performance Space Computingproject. HPSC is led by the agency’s Space Technology Mission Directorate’s Game Changing Development program with support from the Science Mission Directorate. The project is led by JPL, a division of Caltech.
stuart888
Regular
Big deal here, way to go @Fullmoonfever as the education focus should be front and center. Edge Impulse seems to master the education focus already. What a huge event to help in the education of future Akida SNN publishers.Just saw the article as well.
Back to Newsroom
BrainChip Empowers Next Generation of Technology Innovators with Launch of the University AI Accelerator Program
Tuesday, August 16, 2022 5:30 PM
Brainchip Holdings Limited/ADR
Home
Unlock the power of AI with BrainChip. Enhance data processing, Edge apps and neural networks at the speed of tomorrow. Explore now!
Share this Article
Topic:
Product Announcements
LAGUNA HILLS, CA / ACCESSWIRE / August 16, 2022 / BrainChip Holdings Ltd (ASX:BRN) (OTCQX:BRCHF) (ADR:BCHPY), the world's first commercial producer of neuromorphic AI IP, is bringing its neuromorphic technology into higher education institutions via the BrainChip University AI Accelerator Program, which shares technical knowledge, promotes leading-edge discoveries and positions students to be next-generation technology innovators.
BrainChip's University AI Accelerator Program provides hardware, training, and guidance to students at higher education institutions with existing AI engineering programs. BrainChip's products can be leveraged by students to support projects in any number of novel use cases or to demonstrate AI enablement. Students participating in the program will have access to real-world, event-based technologies offering unparalleled performance and efficiency to advance their learning through graduation and beyond.
The Program successfully completed a pilot session at Carnegie Mellon University this past spring semester and will be officially launching with Arizona State University in September. There are five universities and institutes of technology expected to participate in the program during its inaugural academic year. Each program session will include a demonstration and education of a working environment for BrainChip's AKD1000 on a Linux-based system, combining lecture-based teaching methods with hands-on experiential exploration.
"We have incorporated experimentation with BrainChip's Akida development boards in our new graduate-level course, "Neuromorphic Computer Architecture and Processor Design" at Carnegie Mellon University during the Spring 2022 semester," said John Paul Shen, Professor, Electrical and Computer Engineering Department at Carnegie Mellon. "Our students had a great experience in using the Akida development environment and analyzing results from the Akida hardware. We look forward to running and expanding this program in 2023."
BrainChip's first-to-market neuromorphic processor, Akida, mimics the human brain to analyze only essential sensor inputs at the point of acquisition, processing data with unparalleled efficiency, precision, and economy of energy. Keeping AI/ML local to the chip, independent of the cloud, also dramatically reduces latency.
"Universities are looking for the best way to differentiate their curriculum with real-world and hands-on leading-edge technologies," said Sean Hehir, BrainChip's CEO. "By partnering with BrainChip's AI Accelerator Program, universities are able to ensure that students have the tools and resources needed to encourage development of cutting-edge technologies that will continue to usher in an era of essential AI solutions."
Institutions of higher education interested in how they can become members of BrainChip's University AI Accelerator Program can find more details by emailing Sales@brainchip.com.
Getting the SNN IP into the workflow of all the steps on the SoC is a big deal. Let's recruit the entire college community!
PS. We need a better Wow Icon! Wow is better than Fire Icon or Heart Icon. Or is Thinking Icon better, you touched my brain deeply. Icon review!
Attachments
Food4 thought
Regular
InterestingVery interesting.
View attachment 14308
NASA Awards Next-Generation Spaceflight Computing Processor Contract
NASA's Jet Propulsion Laboratory has selected Microchip Technology Inc. to develop a high-performance spaceflight computing processor that will support future space missions.
Credits: NASA
NASA’s Jet Propulsion Laboratory in Southern California has selected Microchip Technology Inc. of Chandler, Arizona, to develop a High-Performance Spaceflight Computing (HPSC) processor that will provide at least 100 times the computational capacity of current spaceflight computers. This key capability would advance all types of future space missions, from planetary exploration to lunar and Mars surface missions.
“This cutting-edge spaceflight processor will have a tremendous impact on our future space missions and even technologies here on Earth,” said Niki Werkheiser, director of technology maturation within the Space Technology Mission Directorate at NASA Headquarters in Washington. “This effort will amplify existing spacecraft capabilities and enable new ones and could ultimately be used by virtually every future space mission, all benefiting from more capable flight computing.”
Microchip will architect, design, and deliver the HPSC processor over three years, with the goal of employing the processor on future lunar and planetary exploration missions. Microchip’s processor architecture will significantly improve the overall computing efficiency for these missions by enabling computing power to be scalable, based on mission needs. The design also will be more reliable and have a higher fault tolerance. The processor will enable spacecraft computers to perform calculations up to 100 times faster than today’s state-of-the-art space computers. As part of NASA's ongoing commercial partnership efforts, the work will take place under a $50 million firm-fixed-price contract, with Microchip contributing significant research and development costs to complete the project.
"We are pleased that NASA selected Microchip as its partner to develop the next-generation space-qualified compute processor platform.” said Babak Samimi, corporate vice president for Microchip’s Communications business unit. “We are making a joint investment with NASA on a new trusted and transformative compute platform. It will deliver comprehensive Ethernet networking, advanced artificial intelligence/machine learning processing and connectivity support while offering unprecedented performance gain, fault-tolerance, and security architecture at low power consumption. We will foster an industry wide ecosystem of single board computer partners anchored on the HPSC processor and Microchip’s complementary space-qualified total system solutions to benefit a new generation of mission-critical edge compute designs optimized for size, weight, and power.”
Current space-qualified computing technology is designed to address the most computationally-intensive part of a mission – a practice that leads to overdesigning and inefficient use of computing power. For example, a Mars surface mission demands high-speed data movement and intense calculation during the planetary landing sequence. However, routine mobility and science operations require fewer calculations and tasks per second. Microchip’s new processor architecture offers the flexibility for the processing power to ebb and flow depending on current operational requirements. Certain processing functions can also be turned off when not in use, reducing power consumption. This capability will save a large amount of energy and improve overall computing efficiency for space missions.
“Our current spaceflight computers were developed almost 30 years ago,” said Wesley Powell, NASA’s principal technologist for advanced avionics. “While they have served past missions well, future NASA missions demand significantly increased onboard computing capabilities and reliability. The new computing processor will provide the advances required in performance, fault tolerance, and flexibility to meet these future mission needs.”
Microchip’s HPSC processor may be useful to other government agencies and applicable to other types of future space mission to explore our solar system and beyond, from Earth science operations to Mars exploration and human lunar missions. The processor could potentially be used for commercial systems on Earth that require similar mission critical edge computing needs as space missions and are able to safely continue operations if one component of the system fails. These potential applications include industrial automation, edge computing, time-sensitive ethernet data transmission, artificial intelligence, and even Internet of Things gateways, which bridge various communication technologies.
In 2021, NASA solicited proposals for a trade study for an advanced radiation-hardened computing chip with the intention of selecting one vendor for development. This contract is part of NASA’s High-Performance Space Computingproject. HPSC is led by the agency’s Space Technology Mission Directorate’s Game Changing Development program with support from the Science Mission Directorate. The project is led by JPL, a division of Caltech.
But will that help Brainchip?
I know we have a connection with microchip but will that turn into revenue for brainchip?
What happened with Brainchip being involved with NASA ?
TechGirl
Founding Member
Hi F4T,
BrainChip are still involved with NASA, the NASA logo is still on BrainChip's home page.
We may be involved with this MicroChip deal or we may not be, but I am sure there is plenty of room at NASA for the both of us.
Frank Zappa
Regular
There will be a lot of shorting today . Bank of America is recommending it to be done NOW
Simon Thorpe has been researching NNs for decades.
https://cerco.cnrs.fr/page-perso-simon-thorpe/
My current interests are centered on understanding the phenomenal processing speed achieved by the visual system. For a number of years we have been running experiments that attempt to measure just how fast visual processing is using briefly flashed natural scenes using a combination of electrophysiological and behavioural methods. With Holle Kirchner, we recently found that when two images are simultaneously flashed to the left and right of the fixation point, humans can initiate saccades to the side where the scene contains an animal in only 130 ms. Such severe temporal constraints pose major problems for virtually all current theories of visual processing. In an attempt to explain this sort of ultra-rapid processing I proposed a novel coding scheme that uses the order in which cells fire spikes, rather than firing rates to encode information. It turns out that using such a code may allow us recognise objects when as few as 1% of the neurons in the visual pathways have fired a spike. In 1999, I setup a company (SpikeNet Technology) that has developed image processing software based on these principles. A demo of the software can be downloaded from the company web site (www.spikenet-technology.com).
I have recently become interested in questions of the economy and tax reform. You can find out more about my radical ideas here.
db1969oz
Regular
Could you please explain what this means? Unfortunately I’m not experienced enough with shorting, or Bank of America to know exactly what you are saying? Cheers.
Frank Zappa
Regular
At work . Will post later
chapman89
Founding Member
Wasn’t the ZMOD4410 one that’s was suspected to have akida in it?
sponsored by
Reducing power consumption in battery-powered devices
Many devices in IoT-based systems are designed with a small form factor and are battery powered. Battery replacement in a commercial infrastructure usually involves the dismantling and refitting of electronic components, including the sensors that form the backbone of Internet of Things (IoT) technology. Such efforts consume a substantial amount of time and manpower, as a commercial building network may contain thousands of these devices. This makes energy-efficient, battery-powered, portable sensors and actuators the most acceptable solution for retrofitting operations. Increasing the battery life of these sensors improves system reliability by reducing the downtime caused by a single node running out of battery. This article discusses the energy consumption challenges that IoT devices face and possible solutions, including the use of ultra-low power sensors.
Energy usage in wireless sensors
With the rise of IoT, embedded designers are more than ever focusing their attention and efforts on system energy usage. One example of a purpose-built product in this regard is a battery-powered wireless sensor node. The operation of a wireless sensor comprises a series of events, with each event requiring a certain amount of power. These events include:
Figure 1: Power consumption in battery-powered sensors during their three main states
Source: eenewsanalog.com
There are multiple techniques and design strategies designed to decrease power consumption and optimize power-saving performance: hardware or software energy optimization, network optimization, and energy harvesting.
Hardware Optimization
Design engineers can choose microcontroller units (MCUs) that are designed specifically for low-energy consumption. An MCU, however, isn’t the only potential energy hog in an IoT device. Opting for low-power sensors and nodes can also substantially reduce power consumption.
Network Optimization
Choosing a connectivity solution for any IoT device depends heavily on the application’s chosen components, the performance of the connected objects, and their energy consumption. IoT applications with low power requirements can make use of Low Power Wide Area Network (LPWAN) for long-distance connectivity, while battery-powered IoT devices can use Bluetooth Low Energy (BLE) for short to-medium communication ranges. The distance between two nodes, system topology, data rate, and the message size are all factors that influence the transmission time, which in turn impacts power consumption.
Optimizing software for low power consumption
Programming the device to run in low power modes, rather than active modes, will make a significant difference in conserving battery power. New developments in low power management have introduced a wide range of ultra-low-power sleep modes. Whereas previous devices have only differentiated between run and idle modes, current devices feature more levels of granularity, including standby, doze, sleep, and deep sleep. Applications are programmed to spend as little time as possible in the MCU’s active mode. This might mean simplifying calculations, batching operations, or transitioning to an asynchronous and interrupt-driven design.
Applications
Weather Station Solution
Figure 2: IoT-based Indoor Air Quality measurement
Source: Renesas
This weather station solution supports smart home and agriculture systems where an indoor controller unit aggregates weather data (temperature, humidity, and CO2concentration). The weather data is measured by an outdoor unit that is solar powered and features an ultra-low-power MCU. The indoor and outdoor units are connected via BLE, and captured data is communicated to the Cloud via Wi-Fi. Renesas’ ZMOD Digital Gas Sensor family uses embedded artificial intelligence (AI) technology and leverages different Operating Modes, which use time, temperature, and gas signatures that enable unique signals from a highly trained machine learning (ML) system. The outdoor unit is controlled by an ultra-low power RE01 MCU. The indoor unit is controlled by an RX-based 32-bit MCU with added security features that make it suitable for cloud communication.
IoT Cold Chain Monitoring
Figure 3: IoT-based Cold Chain Monitoring
Many industries, including agriculture, pharmaceuticals, and logistics require refrigerated storage for their products and ingredients. An IoT-based cold chain monitoring solution allows temperature and humidity to be measured from a remote location, with alerts set up for temperature changes and anomalies, preventing waste and spoilage as ingredients move through the supply chain. The system is controlled by a Renesas RA4W1 32-bit MCU, using Bluetooth LE 5.0 for wireless communications. Sensors include the ZMOD4410 indoor air quality sensor and the HS3001 temperature and humidity sensor.
Low-power sensors from Renesas
ZMOD4410 Indoor Air Quality Sensor
Buy Now
The ZMOD4410 gas sensor module is designed to detect total volatile organic compounds (TVOCs), estimate CO2, and monitor indoor air quality. The sensor communicates via its built-in I2C interface. To reduce power, gas sensors can be operated in various modes, such as continuous temperature operation or duty cycling. The ZMOD4410 Indoor Air Quality Sensor offers two power modes: Continuous and Low Power. When “Continuous” is selected, the measurement is performed continuously. When “Low Power” is selected, measurements are taken in intervals of 5475 ms. The average power consumption in Low Power mode is 0.16mW.
ZMOD4510 Outdoor Air Quality Platform
Buy Now
The ZMOD4510 Outdoor Air Quality (OAQ) Platform is a gas sensor system that can be used in a variety of indoor and outdoor applications. The ZMOD4510 uses machine learning and traditional methods to determine Air Quality Index (AQI), which is based on concentrations of gases in the atmosphere, including nitrogen dioxide (NO). The ZMOD4510 currently has two released operation modes.
Table 1: Air Quality Index Levels Described by the EPA
Operation Mode 1 allows a general measurement of Air Quality (AQ), including the non-selective measurement of NO2 and O3. The AQI is determined based on the classifications by the EPA (Environmental Protection Agency) for O3 and NO2 levels (Table 1).
Operation Mode 2 allows the selective measurement of O3 with a fast sample rate of two seconds. With an average consumption of 0.2mW, power consumption is minimal. The second-generation OAQ algorithm is specifically designed to detect ozone, and the cross-sensitivity response to NO2 is reported as less than 25 AQI, even at NO2 levels up to 200ppb.
Table 2: Gas Sensor Module Specifications during Operation
HS3001 Humidity and Temperature Sensor
Buy Now
Renesas’ HS3001 sensor is a MEMS-based relative humidity and temperature sensor. It features fast measurement response time (typically 6 seconds) with high accuracy. The HS300x is factory-programmed to operate in Sleep Mode. In Sleep Mode, the sensor waits for commands from the controller before taking any measurements. The digital core only performs conversions when it receives a measurement request command (MR); otherwise, it remains powered down. It consumes a minimal amount of power: an average of 1.0µA with one RH+T measurement per second, 8-bit resolution, and a 1.8V supply. Its low power consumption, along with its small form factor (3.0 x 2.4 x 0.8 mm), make it well suited for use in portable, battery-operated devices.
Sensors
Shop our wide variety of Sensors by Renesas.
Shop Now
Don't forget to take our poll.
Summing up: Low power sensors for IoT
Power consumption plays an important role in IoT devices and nearly all embedded devices. Choosing components capable of running at reduced power, including MCUs, power sources, communication protocols, and sensors, diminishes power consumption concerns. Sensors are the primary element of any IoT-based system and should ideally consume minimal power without compromising their static and dynamic characteristics. Renesas offers a variety of sensors that are designed for use in IoT systems and feature low power operation modes that greatly extend the life of battery-powered devices.
Do You Use Ultra-Low Power Sensors to Extend Battery Life?
Take the Poll | Join our Discussionsponsored by
Reducing power consumption in battery-powered devices
Many devices in IoT-based systems are designed with a small form factor and are battery powered. Battery replacement in a commercial infrastructure usually involves the dismantling and refitting of electronic components, including the sensors that form the backbone of Internet of Things (IoT) technology. Such efforts consume a substantial amount of time and manpower, as a commercial building network may contain thousands of these devices. This makes energy-efficient, battery-powered, portable sensors and actuators the most acceptable solution for retrofitting operations. Increasing the battery life of these sensors improves system reliability by reducing the downtime caused by a single node running out of battery. This article discusses the energy consumption challenges that IoT devices face and possible solutions, including the use of ultra-low power sensors.
Energy usage in wireless sensors
With the rise of IoT, embedded designers are more than ever focusing their attention and efforts on system energy usage. One example of a purpose-built product in this regard is a battery-powered wireless sensor node. The operation of a wireless sensor comprises a series of events, with each event requiring a certain amount of power. These events include:
- Waking up, measuring the relevant parameters, and processing the data into messages
- Powering up the radio frequency amplifier, transmitting the messages, and powering down the radio frequency power amplifier
Figure 1: Power consumption in battery-powered sensors during their three main states
Source: eenewsanalog.com
There are multiple techniques and design strategies designed to decrease power consumption and optimize power-saving performance: hardware or software energy optimization, network optimization, and energy harvesting.
Hardware Optimization
Design engineers can choose microcontroller units (MCUs) that are designed specifically for low-energy consumption. An MCU, however, isn’t the only potential energy hog in an IoT device. Opting for low-power sensors and nodes can also substantially reduce power consumption.
Network Optimization
Choosing a connectivity solution for any IoT device depends heavily on the application’s chosen components, the performance of the connected objects, and their energy consumption. IoT applications with low power requirements can make use of Low Power Wide Area Network (LPWAN) for long-distance connectivity, while battery-powered IoT devices can use Bluetooth Low Energy (BLE) for short to-medium communication ranges. The distance between two nodes, system topology, data rate, and the message size are all factors that influence the transmission time, which in turn impacts power consumption.
Optimizing software for low power consumption
Programming the device to run in low power modes, rather than active modes, will make a significant difference in conserving battery power. New developments in low power management have introduced a wide range of ultra-low-power sleep modes. Whereas previous devices have only differentiated between run and idle modes, current devices feature more levels of granularity, including standby, doze, sleep, and deep sleep. Applications are programmed to spend as little time as possible in the MCU’s active mode. This might mean simplifying calculations, batching operations, or transitioning to an asynchronous and interrupt-driven design.
Applications
Weather Station Solution
Figure 2: IoT-based Indoor Air Quality measurement
Source: Renesas
This weather station solution supports smart home and agriculture systems where an indoor controller unit aggregates weather data (temperature, humidity, and CO2concentration). The weather data is measured by an outdoor unit that is solar powered and features an ultra-low-power MCU. The indoor and outdoor units are connected via BLE, and captured data is communicated to the Cloud via Wi-Fi. Renesas’ ZMOD Digital Gas Sensor family uses embedded artificial intelligence (AI) technology and leverages different Operating Modes, which use time, temperature, and gas signatures that enable unique signals from a highly trained machine learning (ML) system. The outdoor unit is controlled by an ultra-low power RE01 MCU. The indoor unit is controlled by an RX-based 32-bit MCU with added security features that make it suitable for cloud communication.
IoT Cold Chain Monitoring
Figure 3: IoT-based Cold Chain Monitoring
Many industries, including agriculture, pharmaceuticals, and logistics require refrigerated storage for their products and ingredients. An IoT-based cold chain monitoring solution allows temperature and humidity to be measured from a remote location, with alerts set up for temperature changes and anomalies, preventing waste and spoilage as ingredients move through the supply chain. The system is controlled by a Renesas RA4W1 32-bit MCU, using Bluetooth LE 5.0 for wireless communications. Sensors include the ZMOD4410 indoor air quality sensor and the HS3001 temperature and humidity sensor.
Low-power sensors from Renesas
ZMOD4410 Indoor Air Quality Sensor
Buy Now
The ZMOD4410 gas sensor module is designed to detect total volatile organic compounds (TVOCs), estimate CO2, and monitor indoor air quality. The sensor communicates via its built-in I2C interface. To reduce power, gas sensors can be operated in various modes, such as continuous temperature operation or duty cycling. The ZMOD4410 Indoor Air Quality Sensor offers two power modes: Continuous and Low Power. When “Continuous” is selected, the measurement is performed continuously. When “Low Power” is selected, measurements are taken in intervals of 5475 ms. The average power consumption in Low Power mode is 0.16mW.
ZMOD4510 Outdoor Air Quality Platform
Buy Now
The ZMOD4510 Outdoor Air Quality (OAQ) Platform is a gas sensor system that can be used in a variety of indoor and outdoor applications. The ZMOD4510 uses machine learning and traditional methods to determine Air Quality Index (AQI), which is based on concentrations of gases in the atmosphere, including nitrogen dioxide (NO). The ZMOD4510 currently has two released operation modes.
| Air Quality Index (AQI) | Level of Concern and Air Quality Condition | O3Concentration 1h average [ppb][a] | O3Concentration 8h average [ppb] | NO2Concentration 1h average [ppb] | Color Code |
|---|---|---|---|---|---|
| 0 to 50 | Good | 0 to 62 | 0 to 54 | 0 to 53 | Green |
| 51 to 100 | Moderate | 63 to 124 | 55 to 70 | 54 to 100 | Yellow |
| 101 to 150 | Unhealthy for Sensitive Groups | 125 to 164 | 71 to 85 | 101 to 360 | Orange |
| 151 to 200 | Unhealthy | 165 to 204 | 86 to 105 | 361 to 649 | Red |
| 201 to 300 | Very Unhealthy | 205 to 404 | 106 to 200 | 650 to 1249 | Purple |
| 301 to 500 | Hazardous | 405 to 604 | - | 1250 to 2049 | Maroon |
Operation Mode 1 allows a general measurement of Air Quality (AQ), including the non-selective measurement of NO2 and O3. The AQI is determined based on the classifications by the EPA (Environmental Protection Agency) for O3 and NO2 levels (Table 1).
Operation Mode 2 allows the selective measurement of O3 with a fast sample rate of two seconds. With an average consumption of 0.2mW, power consumption is minimal. The second-generation OAQ algorithm is specifically designed to detect ozone, and the cross-sensitivity response to NO2 is reported as less than 25 AQI, even at NO2 levels up to 200ppb.
| Symbol | Parameter | Conditions | Min | Typical | Max | Unit |
|---|---|---|---|---|---|---|
| Average Power: OAQ 1st Gen | Outdoor Air Quality | ---- | 21 | ---- | mW | |
| Average Power: OAQ 2nd Gen | Selective ozone with ultra-low power | ---- | 0.2 | ---- | mW | |
| IACTIVE | Supply Current, Active Mode including Heater Current for OAQ 1st Gen | At VDD = 1.8 V | ---- | 11 | 13 | mA |
| At VDD = 3.3 V | ---- | 08 | 10 | mA | ||
| IACTIVE | Supply Current, Active Mode including Heater Current for OAQ 2nd Gen | At VDD = 1.8 V | ---- | 10 | 12 | mA |
| At VDD = 3.3 V | ---- | 6 | 8 | mA | ||
| ISLEEP | Current during measurement delays | Sleep Mode ASIC | ---- | 450 | ---- | mA |
HS3001 Humidity and Temperature Sensor
Buy Now
Renesas’ HS3001 sensor is a MEMS-based relative humidity and temperature sensor. It features fast measurement response time (typically 6 seconds) with high accuracy. The HS300x is factory-programmed to operate in Sleep Mode. In Sleep Mode, the sensor waits for commands from the controller before taking any measurements. The digital core only performs conversions when it receives a measurement request command (MR); otherwise, it remains powered down. It consumes a minimal amount of power: an average of 1.0µA with one RH+T measurement per second, 8-bit resolution, and a 1.8V supply. Its low power consumption, along with its small form factor (3.0 x 2.4 x 0.8 mm), make it well suited for use in portable, battery-operated devices.
Sensors
Shop our wide variety of Sensors by Renesas.
Shop Now
Don't forget to take our poll.
Summing up: Low power sensors for IoT
Power consumption plays an important role in IoT devices and nearly all embedded devices. Choosing components capable of running at reduced power, including MCUs, power sources, communication protocols, and sensors, diminishes power consumption concerns. Sensors are the primary element of any IoT-based system and should ideally consume minimal power without compromising their static and dynamic characteristics. Renesas offers a variety of sensors that are designed for use in IoT systems and feature low power operation modes that greatly extend the life of battery-powered devices.
db1969oz
Regular
Thanks.
Similar threads
