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Renesas Will Demonstrate the First Working Silicon Based on the Recently Debuted Arm Cortex-M85 Processor
Renesas will present the first live demonstration of an MCU based on the recently announced Arm® Cortex®-M85 processor at Embedded World June 21-23.
www.businesswire.com
Renesas Will Demonstrate the First Working Silicon Based on the Recently Debuted Arm Cortex-M85 Processor
Microcontroller Leader to Showcase Performance, High Integration and Security Advances at Embedded World 2022 Exhibition and Conference
(Graphic: Business Wire)
TOKYO--(BUSINESS WIRE)--Renesas Electronics Corporation (TSE:6723), a premier supplier of advanced semiconductor solutions, today announced that it will present the first live demonstration of a microcontroller (MCU) based on the recently announced Arm® Cortex®-M85 processor. The demonstration will take place in the Renesas booth - Hall 1, Stand 234 (1-234) at the Embedded World 2022 Exhibition and Conference in Nuremburg Germany from June 21-24.
Renesas introduced the RA (Renesas Advanced) Family of Arm Cortex-M based MCUs in October of 2019, entering the general-purpose Arm-Cortex-M market with a robust and feature rich family of flash-based MCUs. In roughly 30 months, Renesas has quickly taken a leadership position, introducing 17 MCU groups encompassing well over 200 individual parts. In addition, Renesas has developed a robust ecosystem of partners providing customers with comprehensive solutions for IoT, AI/ML, industrial automation, medical, building automation, home appliance and multiple other applications.
“As a lead partner with Arm, we are proud to be the first to demonstrate an MCU based on the high-performance Cortex-M85 processor, a clear example of the momentum that we have built in the Arm ecosystem,” said Roger Wendelken, Senior Vice President in Renesas’ IoT and Infrastructure Business Unit. “The RA family has enjoyed tremendous success in a very short time, demonstrating the core strengths that make Renesas an MCU powerhouse, including design expertise, legendary quality, and close collaboration with customers and partners in all markets and all geographies.”
“To continue to scale and grow, the next generation of IoT solutions demand ever-improving levels of performance, security and simplified development, and we have delivered this with the new Arm Cortex-M85,” said Dipti Vachani, senior vice president and general manager, Automotive and IoT Line of Business at Arm. “This demonstration of the first silicon based on our most secure and highest performance Cortex-M processor will showcase the new and exciting applications it will enable and further cements our ongoing close collaboration with Renesas.”
The Arm Cortex-M85 processor features Helium technology, Arm’s M-Profile Vector Extension that enables advanced DSP/ML capabilities and helps accelerate compute intensive applications such as endpoint AI. Delivering over 6 CoreMark/MHz, Cortex-M85 enables demanding IoT use cases that require the highest compute performance and DSP or ML capability, realized on a single, simple-to-program, Cortex-M processor. Cortex-M hallmarks such as deterministic operation, short interrupt response time, and state-of-the-art low-power support are uncompromised on Cortex-M85.
Renesas is developing a new series of RA MCUs based on the Cortex-M85 processor, planned for release in 2023. These new RA family MCUs will provide breakthrough performance and fully deterministic, low latency, real-time operation for demanding application needs across numerous markets. The new RA devices will bridge the gap between MCUs and MPUs, enabling complex and compute-intensive applications with the lower power consumption and ease of use of an MCU. This will help customers preserve their investment in software development and reduce costs of migration to an MPU based system. As with other RA MCUs, the new devices will offer best-in-class peripherals, memory and low power consumption.
The new Cortex-M85 core based on Armv8-M architecture supports Arm TrustZone® technology for protection of secure assets. Combined with TrustZone, Renesas’ integrated cryptographic engine, immutable storage, key management, and tamper protection against DPA/SPA side-channel attacks will provide a comprehensive and fully integrated secure element functionality. The Armv8-M architecture also brings Pointer Authentication/Branch Target Identification (PAC/BTI) security extension, a new architectural feature that provides enhanced mitigation from software attack threats and helps achieve PSA Certified Level 2 certification.
The new RA MCUs based on the Cortex-M85 core will be supported by Renesas’ Flexible Software Package (FSP). The FSP enables faster application development by providing all the infrastructure software needed, including multiple RTOS, BSP, peripheral drivers, middleware, connectivity, networking and security stacks as well as reference software to build complex AI, motor control and graphics solutions. It allows customers to integrate their own legacy code and choice of RTOS with FSP, thus providing full flexibility in application development. Using the FSP will ease migration of existing designs to the new RA devices.
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Edge Machine Learning for Anomaly Detection and Predictive Maintenance (ft. Renesas) | InnoTalks
Explore edge machine learning for anomaly detection and predictive maintenance. With the advent of more powerful and cost-effective computing, the marriage of maintenance strategies including reactive, preventive, and predictive maintenance has propelled us into the next great era of digital...
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ARM battles RISC-V at Renesas
Dr. Sailesh Chittipeddi, Executive Vice President and General Manager of IoT and Infrastructure Business Unit of Renesas Electronics talks to eeNews Europe
www.eenewseurope.com
ARM battles RISC-V at Renesas
Interviews | May 27, 2022Renesas Electronics is looking to catch up in the ARM microcontroller and processor markets, but also looking at the emerging RISC-V cores and new spiking AI accelerators to boost machine learning in the Internet of Things (IoT). At the same time a deal with Arduino aims to drive its chips…
By Nick Flaherty
Share:
Renesas Electronics is looking to catch up in the ARM microcontroller and processor markets, but also looking at the emerging RISC-V cores and new spiking AI accelerators to boost machine learning in the Internet of Things (IoT).
At the same time a deal with Arduino aims to drive its chips into many more areas, says Dr. Sailesh Chittipeddi, Executive Vice President and General Manager of IoT and Infrastructure Business Unit of Renesas Electronics talking to eeNews Europe.
“We’ve been doing a lot over the last several years,” said Chittipeddi. “We are primarily strengthening our microcontroller and microprocessor core capabilities which is the heart and soul of the business. We had fallen behind in the ARM ecosystem and we had a strong push to catch up and we have been. We are a long way from being the leader in this market, but the early indicators are good,” he said.
This desire to catch up is reflected by the showing of the first device using the ARM Cortex-M85 core, the highest performance microcontroller core, at Embedded World next month. But with the recent acquisitions of Dialog Semiconductor in the UK and Celeno in Israel the company is adding more wireless capabilities as well as a whole new FPGA business.
- Renesas launches 64bit RISC-V microprocessors with ARM compatible pinout
- Renesas to show first ARM M85 silicon
- Renesas boosts entry level ARM controller performance
The company is used to dealing with multiple instruction set architectures. Over the years it has subsumed the Hitachi SuperH and Mitsubishi microcontroller technologies into its own proprietary families alongside a wide range of ARM-based devices.
“So the other side, we’ve introduced our first RISC-V based products as well into the marketplace, which is actually quite exciting from my perspective. And one of the main reasons why we went ahead with the RISC-V products as opposed to test chips, which a lot of people spoke about was really to make sure that we didn’t fall behind,” he said.
The first 32bit cores and devices are targeted at specific applications. “One being the motor controller and the other being the voice based device. So those two are first two products but we will have a portfolio of products which will introduce over the next several years for certain target markets,” he said.
“On the MPU side that was a major reboot because that business is primarily focused on ASICs and high end R-Car devices. So what we did do is we did a major pivot again about roughly about three years ago to go after two categories of products. One is the general purpose microprocessor, which is a 64 bit microprocessor and ranging from the A53 all the way to A72AE [safety critical] cores.
The other side is the embedded AI with DRP dynamically reconfigurable processor for vision solutions. That’s a feedforward neural network rather than a convolutional neural network (CNN), and it offers reasonable 0.5TOPS to 10TOPS at very low power compared to day the Nvidia or Intel equivalent. From my perspective RISC-V will evolve into that areas in the not too distant future.
“So that’s kind of the plan that we have, to evolve that into that landscape,” he said. “At the very low end, we have added an ARM M33 MCU and spiking neural network with BrainChip core licensed for selected applications – we have licensed what we need to license from BrainChip including the software to get the ball rolling.”
“The MPU with RISC-V allows us to go int a new class of applications,” he said. “With RISC-V its all a question of time. I do see ARM now offering custom instructions but I do see the open ecosystem starting to play a role with the geopolitical tensions and that will provide some necessary impetus in certain regions to head in that direction and that will the ecosystem
“To ARM’s credit the ecosystem they have developed is unparalleled and it would be difficult for RISC-V to catch up even with all its strong backing, it’ll take quite a bit of time.”
So Renesas has deals with both Andes and SiFive for RISC-V cores.
“For us to get to the market quickly we went with the Andes cores on the microcontrollers and we partnered with SiFive. It’s not that we are confused, its about the time to market and internally we are developing our own optimised architectures, and the software that needs to be developed we are doing in parallel.”
Security is also vital with the UK as a key design centre. “We are spending a lot of time on security particularly side channel attacks, tamper resistance, going beyond ARM’s TrustZone,” he said. “ At the moment we think our internal efforts are leading with centres in the UK and Japan and obviously edge devices are more vulnerable.”
- Renesas, WolfSSL team for free embedded IoT security license
- Renesas seals $6bn Dialog deal – update
- Renesas enters the FPGA business
“The issues with CPUs is they are single threaded in general and the option to multithread is to add cores. The nice thing about FPGAs is they allow multithreading but with expense and more complex software. So what Dialog did with GreenPak was come up with a configurable engine with 5000 gates or 1000 to 2000 look up tables and drawing 20uA and a cost of 50c or below at high volume so you can see why it is well positioned against a typical multicore CPU. This kind of moves more towards a faster approach in that direction We don’t complete with Intel or AMD or Lattice or Microchip, they have much more horsepower.
The tools are an important element for the ease of development. “With the software we offer both HDL and the more traditional Verilog approaches but the nice thing about GreenPak was the GUI was easy to use and we are taking a very similar approach for the Forge FPGA so its an easy to use GUI that will be very similar for the users of GreenPak to adopt and you can copackage a Forge FPGA with a GreenPak state machine. Down the pike you can see an integrated solution.”
Many of the microcontrollers are built on legacy process technologies that suit the analog and mixed signal peripherals, rather than the leading edge technologies. However the pressure on these legacy process technologies have been one of the key factors in the chip shortage.
“We are well equipped with our foundry partners, especially at 40nm and 25nm which continue to be tight but the bulk of MCU and MPU is internal capacity on 40, 25 and 22nm which is where we will be over the next few years,” he said. “At 28 to 180nm in foundry, that’s the tightest in the world and that will take another couple of years to free up given the lead times for the equipment are stretching to 30 months up from 18 months. It will take quite some time for even the greenfield projects to come on line so there will be glut in capacity in time but the good thing in general is there are corrections in the market but the overall semiconductor consumption is going up massively in automotive and industrial automation and digitalisation, that’s driving a lot of long term growth,” he said.
“We are still a way away from a 3nm world. Our most advanced MPUs are 7/5nm but that’s driven by high end applications largely in the industrial ecosystem. What we are doing for the first time is going to the 1-2GHz range with general purpose MPUs and we will be getting to that level of performance on MCUs but that can be at a node that’s a level behind
He plans to have an MCU running over 1GHz next year but it is the mix of cores that is key as well as connectivity.
“We are moving to a world that’s less CPU or MPU to more AI centric and that will drive changes with intelligence moving to the edge,” he said. “That’s an important trend, driving the need for maximum compute at the lowest power consumption.
“For us one of the weak points was connectivity as we were trying to do it all in-house,” he said. “Dialog gave us the low power for wearables, earbuds and headsets and they had a 2.4GHz solution for low power WiFi. We felt we needed a path to WiFi5 and 6, 6E as we see 6E having a bigger role in industrial hence the Israel deal and that gives us 2.4GHz, 5GHz and 6GHz. With MCUs you need access to the cloud, you need seamless access to the cloud.”
The Arduino deal is also key he says.
“We have formed a strategic partnership with Arduino as they have this base of 30m users and by working with them we think we have a good opportunity for MCUs, sensors, power and connectivity,” he said. “I think Arduino will move into a broader application space by working with an outfit such as us with our base of industrial customers and they have their roadmaps to expand so we have an opportunity to work with them. Even if its hobbyist it’s a pathway to get university students hooked on Arduino today and they will be the engineers tomorrow making the buying decisions.
Dougie54
Regular
JUST WOW,Awesome readingARM battles RISC-V at Renesas
Dr. Sailesh Chittipeddi, Executive Vice President and General Manager of IoT and Infrastructure Business Unit of Renesas Electronics talks to eeNews Europe
ARM battles RISC-V at Renesas
Interviews | May 27, 2022
Renesas Electronics is looking to catch up in the ARM microcontroller and processor markets, but also looking at the emerging RISC-V cores and new spiking AI accelerators to boost machine learning in the Internet of Things (IoT). At the same time a deal with Arduino aims to drive its chips…
By Nick Flaherty
Share:
Renesas Electronics is looking to catch up in the ARM microcontroller and processor markets, but also looking at the emerging RISC-V cores and new spiking AI accelerators to boost machine learning in the Internet of Things (IoT).
At the same time a deal with Arduino aims to drive its chips into many more areas, says Dr. Sailesh Chittipeddi, Executive Vice President and General Manager of IoT and Infrastructure Business Unit of Renesas Electronics talking to eeNews Europe.
“We’ve been doing a lot over the last several years,” said Chittipeddi. “We are primarily strengthening our microcontroller and microprocessor core capabilities which is the heart and soul of the business. We had fallen behind in the ARM ecosystem and we had a strong push to catch up and we have been. We are a long way from being the leader in this market, but the early indicators are good,” he said.
This desire to catch up is reflected by the showing of the first device using the ARM Cortex-M85 core, the highest performance microcontroller core, at Embedded World next month. But with the recent acquisitions of Dialog Semiconductor in the UK and Celeno in Israel the company is adding more wireless capabilities as well as a whole new FPGA business.
With the future of ARM uncertain with the failed Nvidia bid and now a public offering, the company is also looking at the RISC-V alternative through deals with Andes Technology and SiFive as well as its own internal development.
- Renesas launches 64bit RISC-V microprocessors with ARM compatible pinout
- Renesas to show first ARM M85 silicon
- Renesas boosts entry level ARM controller performance
The company is used to dealing with multiple instruction set architectures. Over the years it has subsumed the Hitachi SuperH and Mitsubishi microcontroller technologies into its own proprietary families alongside a wide range of ARM-based devices.
“So the other side, we’ve introduced our first RISC-V based products as well into the marketplace, which is actually quite exciting from my perspective. And one of the main reasons why we went ahead with the RISC-V products as opposed to test chips, which a lot of people spoke about was really to make sure that we didn’t fall behind,” he said.
The first 32bit cores and devices are targeted at specific applications. “One being the motor controller and the other being the voice based device. So those two are first two products but we will have a portfolio of products which will introduce over the next several years for certain target markets,” he said.
“On the MPU side that was a major reboot because that business is primarily focused on ASICs and high end R-Car devices. So what we did do is we did a major pivot again about roughly about three years ago to go after two categories of products. One is the general purpose microprocessor, which is a 64 bit microprocessor and ranging from the A53 all the way to A72AE [safety critical] cores.
The other side is the embedded AI with DRP dynamically reconfigurable processor for vision solutions. That’s a feedforward neural network rather than a convolutional neural network (CNN), and it offers reasonable 0.5TOPS to 10TOPS at very low power compared to day the Nvidia or Intel equivalent. From my perspective RISC-V will evolve into that areas in the not too distant future.
“So that’s kind of the plan that we have, to evolve that into that landscape,” he said. “At the very low end, we have added an ARM M33 MCU and spiking neural network with BrainChip core licensed for selected applications – we have licensed what we need to license from BrainChip including the software to get the ball rolling.”
“The MPU with RISC-V allows us to go int a new class of applications,” he said. “With RISC-V its all a question of time. I do see ARM now offering custom instructions but I do see the open ecosystem starting to play a role with the geopolitical tensions and that will provide some necessary impetus in certain regions to head in that direction and that will the ecosystem
“To ARM’s credit the ecosystem they have developed is unparalleled and it would be difficult for RISC-V to catch up even with all its strong backing, it’ll take quite a bit of time.”
So Renesas has deals with both Andes and SiFive for RISC-V cores.
“For us to get to the market quickly we went with the Andes cores on the microcontrollers and we partnered with SiFive. It’s not that we are confused, its about the time to market and internally we are developing our own optimised architectures, and the software that needs to be developed we are doing in parallel.”
Security is also vital with the UK as a key design centre. “We are spending a lot of time on security particularly side channel attacks, tamper resistance, going beyond ARM’s TrustZone,” he said. “ At the moment we think our internal efforts are leading with centres in the UK and Japan and obviously edge devices are more vulnerable.”
The recent acquisition of Dialog Semiconductor also brought FPGA technology into the company for the first time.
- Renesas, WolfSSL team for free embedded IoT security license
- Renesas seals $6bn Dialog deal – update
- Renesas enters the FPGA business
“The issues with CPUs is they are single threaded in general and the option to multithread is to add cores. The nice thing about FPGAs is they allow multithreading but with expense and more complex software. So what Dialog did with GreenPak was come up with a configurable engine with 5000 gates or 1000 to 2000 look up tables and drawing 20uA and a cost of 50c or below at high volume so you can see why it is well positioned against a typical multicore CPU. This kind of moves more towards a faster approach in that direction We don’t complete with Intel or AMD or Lattice or Microchip, they have much more horsepower.
The tools are an important element for the ease of development. “With the software we offer both HDL and the more traditional Verilog approaches but the nice thing about GreenPak was the GUI was easy to use and we are taking a very similar approach for the Forge FPGA so its an easy to use GUI that will be very similar for the users of GreenPak to adopt and you can copackage a Forge FPGA with a GreenPak state machine. Down the pike you can see an integrated solution.”
Many of the microcontrollers are built on legacy process technologies that suit the analog and mixed signal peripherals, rather than the leading edge technologies. However the pressure on these legacy process technologies have been one of the key factors in the chip shortage.
“We are well equipped with our foundry partners, especially at 40nm and 25nm which continue to be tight but the bulk of MCU and MPU is internal capacity on 40, 25 and 22nm which is where we will be over the next few years,” he said. “At 28 to 180nm in foundry, that’s the tightest in the world and that will take another couple of years to free up given the lead times for the equipment are stretching to 30 months up from 18 months. It will take quite some time for even the greenfield projects to come on line so there will be glut in capacity in time but the good thing in general is there are corrections in the market but the overall semiconductor consumption is going up massively in automotive and industrial automation and digitalisation, that’s driving a lot of long term growth,” he said.
“We are still a way away from a 3nm world. Our most advanced MPUs are 7/5nm but that’s driven by high end applications largely in the industrial ecosystem. What we are doing for the first time is going to the 1-2GHz range with general purpose MPUs and we will be getting to that level of performance on MCUs but that can be at a node that’s a level behind
He plans to have an MCU running over 1GHz next year but it is the mix of cores that is key as well as connectivity.
“We are moving to a world that’s less CPU or MPU to more AI centric and that will drive changes with intelligence moving to the edge,” he said. “That’s an important trend, driving the need for maximum compute at the lowest power consumption.
“For us one of the weak points was connectivity as we were trying to do it all in-house,” he said. “Dialog gave us the low power for wearables, earbuds and headsets and they had a 2.4GHz solution for low power WiFi. We felt we needed a path to WiFi5 and 6, 6E as we see 6E having a bigger role in industrial hence the Israel deal and that gives us 2.4GHz, 5GHz and 6GHz. With MCUs you need access to the cloud, you need seamless access to the cloud.”
The Arduino deal is also key he says.
“We have formed a strategic partnership with Arduino as they have this base of 30m users and by working with them we think we have a good opportunity for MCUs, sensors, power and connectivity,” he said. “I think Arduino will move into a broader application space by working with an outfit such as us with our base of industrial customers and they have their roadmaps to expand so we have an opportunity to work with them. Even if its hobbyist it’s a pathway to get university students hooked on Arduino today and they will be the engineers tomorrow making the buying decisions.
supersonic001
Regular
Stuart Feffer on LinkedIn: Renesas to Acquire Reality AI to Bring Advanced Signal Processing and… | 34 comments
Today we signed definitive agreements for Reality AI to be acquired by Renesas Electronics. Deal to close upon receiving regulatory… | 34 comments on LinkedIn
SharesForBrekky
Regular
Not sure if this has been posted today but check this out:
Akida could possibly be involved, not too sure. Thoughts?
Akida could possibly be involved, not too sure. Thoughts?
Demo at Embedded World
The DA1470x Family will be demonstrated at Embedded World June 21-23, 2022, in Nuremberg, Germany (hall 1; booth 1-234).Availability
The DA1470x Family consists of four new devices, all of which are in mass production and widely available now.
Stable Genius
Regular
Hi Shares,
I’m still expecting a ”Big Reveal” when Renesas unveil the product with Akida but given they have their own line of AI products maybe they won’t.
I downloaded the specs however it’s 1023 pages: who would have thought that. Unfortunately I couldn’t copy and paste it here the link to it’s on the webpage you provided.
I couldn’t find anything on neural networks or Akida so I’m thinking no which is dissapointing as its on an Arm Cortex M33 which is where I leaning towards Akida being included based on some previous readings.
The videos at the bottom of your links looked ok as well. Key word spotting, ultra low power, learning at the edge:
I did manage to find this but there is still no mention of neural network which given it’s a buzz word at the moment I thought they would be promoting it. Not sure what this ”Sensor node controller” is: (sorry for the way the images are split but I couldn’t work out how to copy it any other way).
Some of the use cases looked interesting. I’m thinking there should be an NPU instead of a CPU on the diagram if it was Akida but technically I really have no idea:
I’m in no way qualified to ogre it so I’ll leave that to Dio.
Good find; we must be getting close and this little family of products would have been awesome!
Edit: I found where I read about Akida being incorporated into an m33 so maybe the nodes are it?
I was just expecting a bit more fan-fare! Maybe that’ll occur on the release/display coming up. Fingers crossed!
Last edited:
SharesForBrekky
Regular
Thanks so much for looking into it SG, very much appreciated.
Yeah doesn't look too promising considering no mention of an NPU being used.
Oh well, it was worth a shot. You never know, Akida could very well be considered in the future with these new devices.
Stable Genius
Regular
It’s bugging me as the information reads as though we are coming out in a family of products soon with the Arm M33 MCU: WHICH IS WHAT IS BEING RELEASED NOW!
I’ve had a look at the Voice Activation Device (VAD) part of the SOC as well but that looks unlikely as well. The part I’ve underlined indicating it adapts itself to the background noise was interesting, but other than than still no mention of SNN or Akida. It’s a bit deflating.
Quatrojos
Regular
Xiaomi Smart Band 7 launches globally, bringing its new always-on display to the masses
It features VO2 and SpO2 monitoring and offers up to 14 days of battery life
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Bit of a long shot here, but I can’t find any news regarding renesas demonstrating the new arm m85 processor and it was meant to be released at the embedded world 2022 which is now over. Maybe just maybe we get an announcement this morning before the big show, but I did say a long shot.
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Join Us at Sensors Converge 2022 | Renesas Electronics
info.renesas.com
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The Role of AI and Endpoint Real-time Data Analytics
Image
Kaushal Vora
Senior Director
The Internet of Things (IoT) has the capability of amassing large amounts of data which it does with the help of dispersed intelligent sensors. The organization and distribution of this enormous amount of data is posing to be a challenge. While conventional methods of data analysis have facilitated the operations in IoT, Artificial Intelligence (AI) has proven that it can do it with greater precision and that too in a lesser timeframe.
The role that AI plays in structuring data is phenomenal. AI is capable of spotting patterns and inconsistencies in real-time. AI algorithms can save significant time by accumulating unstructured data from various sources and processing it in a way so it can be represented in a consistent manner. This makes the process of structuring the data less arduous, thereby offering greater benefit to the stakeholders.
Machine Learning and AI are vital tools that provide secure and predictive analytics in the data centre and beyond. As a result of these predictions, AI will be capable of preventing issues even before they arise, restructure operations, and reduce unforeseen interruptions in the network. Artificial Intelligence when combined with Data Science can assist in structuring a data set, enhance the operations of IoT devices and ultimately reach conclusions in real-time.
AI coupled with Real-time Analytics
In broad terms, real-time analytics refers to the process of preparing, analysing, and assessing data as soon as it is available. AI coupled with real-time analytics has provided businesses with an exceptional insight into the consumer experience. The support personnel and IT workers are now prone to act rather than react, resolving issues before end users even know there is an issue to report. Hence the combination of the two has completely transformed the support experience.According to IDC, an analytics firm, 45% of IoT-created data needs to be analysed closer to the end devices, rather than transmitted to be examined on the cloud. There are several reasons for the shift from the cloud. Transferring data to the cloud has proven to be costly as it requires bandwidth and power to support an interminable data transmission. There is also a potential for latency as a lot of time is expended during transmission, and the necessity for a high server capacity that can handle the data that is coming. There are also instances where the endpoints lack a stable internet connection, and the decision must be made on the endpoint. That is why there is a need for solutions that can support using the analytics at the endpoint. These concerns are of great significance in IoT applications as there is a high dependency on data analytics and real-time decision making and these applications cannot afford being dormant.
Endpoint AoT
‘Analytics of Things’ (AoT) is a term that is used to describe the analysis of data that is generated by the Internet of Things devices. The IoT Analytics of Things makes it possible to operate business intelligence within an application rather than a data warehouse. AoT assists in understanding patterns and analysis for variations, detects anomalies, predicts problems, sets maintenance intervals, and optimizes processes.Over the years, organisations have been relying on data analytics based on centralised architecture for their data-driven planning and future vision. The data is increasing every second and there is a requirement for a revolutionary approach to overcome data transfer latency, improve privacy, and meet customer expectations. The real-time response has especially become important after the convergence of AI, 5G and IoT. All that drives us to develop intelligence at the endpoint.
Distributing intelligence across the most end of the network provides an opportunity for more efficient data analytics and make decisions in real-time, with almost no latency, on the end devices. The solution that can do this with the low processing capabilities, direct on the end devices, is referred to as “Endpoint Data Analytics”.
Image
What is “Data Analytics”?
“Data Analytics” is the science of scrutinizing raw or unprocessed data to derive meaning from it so it can be applied to decision making. Data analytics employs several modern techniques and tools that assist it in structuring and comprehending the data.There are several steps that need to be applied in the process before the actual data analytics can take place:
- The data needs to be interpreted correctly so it may be grouped accordingly.
- Data needs to be collected from various sources
- Data needs to be scrutinized to get rid of any replication or errors.
- Data organization may be done by using tables, spread sheets and numerous statistical methods.
Descriptive Analytics
This describes what has happened over a period. It focuses on summarizing past data to makeinferences.
Image
Diagnostic Analytics
It focuses on understanding and providing answers to why something occurred.Predictive Analytics
It identifies future trends based on given data.Prescriptive Analytics
It allows you to make recommendations of what action should be taken.Support system of Data analytics
Various technologies and sensors facilitate the process of data analytics at the endpoint. Sensors are required to gather and accumulate data to assist in understanding the environment. Examples of sensors include GPS for detecting locations, cameras, lasers, radars, to name a few. Communication technologies assist in transmitting and obtaining the data. The data fuels Data science algorithms which then play a vital part in comprehending the situation. The results from the algorithm processing support the decision-making process. The outcomes of the analytic data can be set as choices on the devices. For instance, the autonomous vehicle has the options of several decisions such as following a planned route, responding to other vehicles on the road, reacting to weather and road conditions and even taking an indirect command if a sudden stop can’t be done safely.To improve the decision-making process, Data analytics will classify the decisions and actions into specific classes. For example, in the case of the autonomous vehicle, it can be defined as operational or tactical class, or strategic in the case of the data lake.
