Organisations in Asia-Pacific are seeking out edge computing in search of faster response and cost savings, but they also have concerns about security and latency when large volumes of data are processed on such platforms.
A primary, and often cited, benefit of edge deployments are the rapid response times that would not be possible if data is sent back to a centralised network for processing.
Taiwan’s Taoyuan City, for instance, turned to edge technology in rolling out smart streetlights in its Qingpu district, using HPE’s Edgeline EL10 Internet of Things (IoT) Gateway.
The Taiwanese city has ambitions of becoming a smart city and is looking to deploy and integrate multi-sensor information from edge products into a centralised platform to deliver better citizen services.
“Certain citizen intelligence applications and services require an almost immediate response time [and] this cannot be achieved if data needs to be transmitted back to a centralised cloud for processing,” a spokesperson for Taoyuan City Government’s Public Works Department told ZDNet.
For applications that operate in an outdoor environment, network connectivity also might be affected by external factors such as weather and road construction, the spokesperson explained, noting that edge computing powered by machine learning algorithms were able to mitigate disruptions in network transmissions.
In addition, processing data via edge technology reduced the amount of information that had to be transmitted over a network, offering cost savings in network and cloud storage, she said.
See: Edge computing: The state of the next IT transformation
To address customer concerns about outdoor or physical attributes, vendors such as HPE have designed their products to withstand various external factors such as dirt, humidity, temperatures, and vibration.
Jason Tan, HPE’s Asia-Pacific general manager of its IoT enterprise solution group, said the vendor’s edge products were built to operate in environments with temperatures as high as 70 degrees Celsius as well as operate “fan-less”, which provides more flexibility in site deployment.
When asked about the initial concerns that the Taoyuan government may experience when deploying the edge technology, the spokesperson pointed to the need to closely monitor such systems.
“Intelligent edge solutions typically require massive data processing and network connectivity. Hence, ensuring regular system updates as well as stability of the various decentralised devices is critical,” she said.
“Furthermore, as citizens increasingly rely more on such services, we need to ensure the data collected from multiple sensor devices is stored properly and securely.”
According to Zhen Ke, principal engineer of Alibaba Cloud’s IoT business unit, customer concerns about the accuracy of edge computing and latency of the cloud network supporting such devices were not uncommon.
As each node operates independently, data disparity and ensuring data is properly synchronised have been cited as potential challenges with regards to edge computing.
Alibaba addressed such concerns by adopting an integrated approach, instead of treating each node as an independent and isolated function, Zhen said.
“While we are empowering the edge, data will still be fed back to the cloud to ensure data consistency and synchronisation. This [will allow users] to tap cloud’s scalability and flexibility to better address dynamic needs,” he said, adding that Alibaba also leveraged AI and machine learning to enhance the entire compute process.
Also: What you need to know before implementing edge computing
Tan noted that HPE’s edge systems supported unmodified enterprise software from its partner community, including Citrix, SAP, GE Digital, and Microsoft. This meant that enterprise customers could use the same application stacks at the edge, in datacentres, as well as cloud.
“[It] simplifies the sharing of critical data and insights from the edge across locations to enable data correlation, deep learning, and process coordination,” he said. “For instance, selected predictive maintenance data from several oil rigs can be aggregated and analysed in a central location to enable intelligent maintenance scheduling across oil rigs.”
He added that the emergence of blockchain technology also paved the away for distributed learning capabilities on edge computing platforms, thereby enabling each node to process their learning and decision making using blockchain and ensure data integrity and consistency.
Key considerations before going to the edge
Taoyuan City’s streetlight management edge deployment is still currently in its pilot phase and the government has plans to deploy more streetlights over the next few phrases of the project, according to the spokesperson.
She noted that the city government is hoping to introduce more innovative services by analysing the data collected in the deployment, spanning parameters such as air quality, climate indicators, and image analysis processing.
In deciding the volume and type of data that should and should not be analysed at the edge, she said the Taoyuan government assessed the network transmission bandwidth of the field device as well as the data management centre.
It also considered the immediacy of the application service, whether it required real-time processing and feedback, and whether edge computing could support the required speed and security, she noted.
She added that, compared to traditional datacentres, outdoor environments are harsher and edge deployments in such situations would need to consider factors such as weather, dust conditions, temperature as well as stability of power supply to the device.
“At the same time, the solution is deployed over a large number of streetlights, which limits resources in terms of processing power and configuration,” she said. “Hence, the ability to analyse the smallest function and need is an important consideration when designing an edge computing deployment.”
Alibaba’s Zhen also noted that edge computing is restricted by its physical limitations of requiring space to house the hardware. Apart from relying on a robust cloud to provide the computing resources required for more intensive processing and analysis, he added that AI is essential to enhance such deployments.
“Edge computing is for business applications requiring speed in processing, response, and action, and AI plays an integral role here,” he said. “Data can typically be analysed at the edge for faster responses and quicker actions, whereas for AI training and analysis, the large volume of data will usually be processed at the cloud.”
Alibaba last month announced a partnership with Intel to jointly develop “data-centric” computing products, including a Joint Edge Computing Platform, which features the chipmaker’s software, hardware, and AI technologies as well as Alibaba Cloud’s IoT offerings.
China’s Chongqing Refine-YuMei Die Casting (YuMei) was the first customer to deploy the new Alibaba-Intel edge product, using the platform to identify defects while parts were cast rather than have to wait until the end of the manufacturing line before they were manually inspected.
AI Edge X: The first 4G Industrial Gateway for AI on the Edge
Bridging the gap between the edge and the cloud in order to bring accelerated vision features and AI performance to the edge of the Internet of Things.
Where’s the ‘edge’ in edge computing? Why it matters, and how we use it
Just as cloud computing seemed to be settling down into a standardized set of platforms, the drive for service differentiation results in new use cases for a faster, more flexible premium service tier. But will those use cases make sense in practice?
The future of edge computing and facial recognition (TechRepublic)
Edge computing will improve industrial processes in manufacturing, and enable facial recognition in retail environments and hotels.
Edge Computing: The 2 things tech leaders should know
IT resources are aggressively being centralized in the cloud, but some cutting edge technologies will need to balance cloud with localized computing power. That’s where edge computing comes in.
2022 BMW M8 Competition range revealed with bigger screens and better lights
German automaker BMW has updated its 2022 M8 Competition sport-luxury car. You can still get an M8 Competition in three body styles (2-door Coupe, 2-door Cabriolet, and 4-door Gran Coupe), sharing the same 4.4-liter twin-turbocharged V8 engine with 617 horsepower and 553 pound-feet of torque.
Images: BMW AG
Tesla Cybertruck delayed again plus Elon Musk squashes $25k EV rumors
Tesla closed out 2021 with a bumper year, besting Q4 estimates and pushing EV deliveries past 300,000, though Elon Musk tempered hopes for the arrival of the Cybertruck and more affordable models. Revenue in the year as a whole grew 71%, Tesla announced, describing 2021 as “a breakthrough year” for the automaker, but some of the most anticipated electric vehicles are still some way out.
No Tesla Cybertruck until 2023
The most conspicuous project that Tesla has underway is undoubtedly the Cybertruck. The oddly-shaped all-electric pickup proved controversial when Elon Musk first revealed it, and glimpses of development prototypes in the intervening years haven’t dimmed its ability to polarize opinion. Undoubtedly the most frequently-asked question, however, is when Tesla actually might put the Cybertruck into production.
Tesla’s investor deck continues with the same, vague timeline as has been stated in previous releases. “We are making progress on the industrialization of Cybertruck, which is currently planned for Austin production subsequent to Model Y,” the automaker says.
Speaking on the investor call, however, Musk confirmed that the Cybertruck wouldn’t go into production this year. The primary focus for Tesla, the CEO explained, would be ramping production of its existing models, like the popular Model 3 and Model Y. They’re still in strong demand, with orders for some configurations of Model Y not expected to be delivered until August 2022.
For the Cybertruck, there are still technological hurdles to be worked through, Musk admitted. The automaker is also still trying to figure out how to make it affordable: there was widespread surprise when Tesla announced the full-size electric pickup would have a starting price of around $40,000 when it began taking reservations in late 2019. For the moment, Musk said, the hope is that production can begin sometime in 2023.
Don’t expect the Tesla Roadster any time soon, either
What goes for the Cybertruck, also goes for Tesla’s rebooted Roadster. Also the spur of no shortage of reservation deposits – or the full $250,000 apiece in advance for those wanting one of the first 1,000 “Founder’s Series” cars – the Roadster was originally intended to go into production in mid to late 2021. That was delayed to 2022, and then to 2023.
The good news is that it’s still, apparently, on track for that timescale, though as Tesla feels the impact of the supply chain issues affecting the whole auto industry that could still change in the meantime. Chip constraints were name-checked by Musk as being a primary bottleneck for 2021 production of its cars, arguing that if Tesla tried to introduce new models in 2022 it would only have the overall impact of cutting total production output. The need to assign resources to new models would take away from the ability to build cars like the Model 3 and Model Y, he pointed out.
Engineering and tooling-up for the upcoming Tesla models may still begin in 2022. However they won’t go into production until 2023 at the earliest.
The $25,000 Tesla isn’t happening
Though Tesla hasn’t been affected by the “market adjustments” that have seen dealers of other brands add thousands or even tens of thousands to the sticker price of a new car, it’s clear that the EV-maker is still focused on the trims with the biggest profit margins. Despite previous chatter of a $25,000 Tesla that could undercut even the most affordable Model 3, Musk says that’s simply not on the cards.
“We have too much on our plate,” the CEO said during the investor call.
The reality is, while Tesla has been surprisingly well placed for dealing with the supply chain crunch – including making admirable use of existing chip supplies by reprogramming its software to suit – like most car companies it can’t build as many as it would like to. Focusing on maximizing the return on each vehicle is the inevitable result, not only by prioritizing the more expensive configurations, but on post-sale software enhancements too. Indeed, “over time, we expect our hardware-related profits to be accompanied with an acceleration of software-related profits,” the investor deck points out.
This carbon 3D-printed Rolls-Royce Cullinan is a $500,000 upgrade
The Cullinan is the Rolls-Royce of SUVs, so what does this make 1016 Industries’ carbon-fiber, 3D-printed Cullinan? You can call it anything you like, but it is indeed a dignified way to go sporty. We highly prefer it over the quirky Mansory Rolls-Royce Cullinan unveiled last year for the 50th founding anniversary of the United Arab Emirates, and it’s all thanks to the crafty use of 3D printing for the details.
Images: 1016 Industries
Biologists name new species of branching worm after legendary King Ghidorah
Enlarge / (left) Biologists have named a newly discovered species of branching worm, Ramisyllis kingghidorahin, after Godzilla’s nemesis. (right) Fragment...
How to fix the Apple ID verification failed error
Is your Apple ID giving you a headache? Many users experience a verification error when trying to sign in to...
Omicron-specific vaccine boosters are now in humans as trials begin
Enlarge / A vial of the current Moderna COVID-19 vaccine. The first doses of omicron-specific COVID-19 vaccines went into the...
Apple just had the biggest holiday quarter in its history
Enlarge / The back of the iPhone 13. Samuel Axon Neither a global pandemic nor a supply chain crunch can...
Apple Q1 2022 winners & losers: iPhone up, iPad down in bumper holiday
Apple has released the earnings report for its first fiscal quarter of 2022, announcing yet another all-time record with revenue...
Social2 years ago
CrashPlan for Small Business Review
Gadgets3 years ago
A fictional Facebook Portal videochat with Mark Zuckerberg – TechCrunch
Mobile3 years ago
Memory raises $5M to bring AI to time tracking – TechCrunch
Cars3 years ago
What’s the best cloud storage for you?
Social3 years ago
iPhone XS priciest yet in South Korea
Security3 years ago
Google latest cloud to be Australian government certified
Social3 years ago
Apple’s new iPad Pro aims to keep enterprise momentum
Cars3 years ago
SK Telecom and Samsung to collaborate on 5G for enterprise