Results


Pervasive AI for IoT Applications: Resource-efficient Distributed Artificial Intelligence

arXiv.org Artificial Intelligence

Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of Things (IoT) applications and services, spanning from recommendation systems to robotics control and military surveillance. This is driven by the easier access to sensory data and the enormous scale of pervasive/ubiquitous devices that generate zettabytes (ZB) of real-time data streams. Designing accurate models using such data streams, to predict future insights and revolutionize the decision-taking process, inaugurates pervasive systems as a worthy paradigm for a better quality-of-life. The confluence of pervasive computing and artificial intelligence, Pervasive AI, expanded the role of ubiquitous IoT systems from mainly data collection to executing distributed computations with a promising alternative to centralized learning, presenting various challenges. In this context, a wise cooperation and resource scheduling should be envisaged among IoT devices (e.g., smartphones, smart vehicles) and infrastructure (e.g. edge nodes, and base stations) to avoid communication and computation overheads and ensure maximum performance. In this paper, we conduct a comprehensive survey of the recent techniques developed to overcome these resource challenges in pervasive AI systems. Specifically, we first present an overview of the pervasive computing, its architecture, and its intersection with artificial intelligence. We then review the background, applications and performance metrics of AI, particularly Deep Learning (DL) and online learning, running in a ubiquitous system. Next, we provide a deep literature review of communication-efficient techniques, from both algorithmic and system perspectives, of distributed inference, training and online learning tasks across the combination of IoT devices, edge devices and cloud servers. Finally, we discuss our future vision and research challenges.


Networking Research for the Arab World

Communications of the ACM

The Arab region, composed of 22 countries spanning Asia and Africa, opens ample room for communications and networking innovations and services and contributes to the critical mass of the global networking innovation. While the Arab world is considered an emerging market for communications and networking services, the rate of adoption is outpacing the global average. In fact, as of 2019, the mobile Internet penetration stands at 67.2% in the Arab world, as opposed to a global average of 56.5%.12 Furthermore, multiple countries in the region are either building new infrastructure or developing existing infrastructure at an unprecedented pace. Examples include, Neom city in Saudi Arabia, the new administrative capital in Egypt, as well as the Smart Dubai 2021 project in the United Arab Emirates (UAE), among others. This provides a unique opportunity to fuse multiple advanced networking technologies as an integral part of the infrastructure design phase and not just as an afterthought.


After US sanctions, Huawei turns to new businesses to boost sales

#artificialintelligence

Six months after the Trump administration dealt a crushing blow to Huawei Technologies Co.'s smartphone business, the Chinese telecommunications giant is turning to less glamorous alternatives that may eventually offset the decline of its biggest revenue contributor. Among its newest customers is a fish farm in eastern China that's twice the size of New York's Central Park. The farm is covered with tens of thousands of solar panels outfitted with Huawei's inverters to shield its fish from excessive sunlight while generating power. About 370 miles to the west in coal-rich Shanxi province, wireless sensors and cameras deep beneath the earth monitor oxygen levels and potential machine malfunctions in mine pit -- all supplied by the tech titan. And next month, a shiny new electric car featuring its lidar sensor will debut at China's largest auto show.


Huawei launches Singapore lab for mobile developers

ZDNet

Huawei Technologies has launched a lab in Singapore to offer mobile developers resources and access to key technologies, including its core kits, artificial intelligence (AI), and augment reality. The Chinese tech giant also is upping its commitment to deliver more localised apps in Singapore, where it saw a 143% jump in new registered developers last year. Led by its mobile arm Huawei Mobile Services (HMS), the new DigiX Lab is located at its local office in Changi Business Park and the first of such facility in Asia-Pacific, the vendor said in a statement Tuesday. It said the lab would support mobile developers throughout the entire app development cycle and its resources would be made available online, accessible virtually across the region. Industry regulator Infocomm Media Development Authority has set aside S$40 million (US$29.53 million) to support research and development efforts and drive adoption of 5G, which include initiatives focused on key verticals such as urban mobility and maritime.


The Relationship Between 5G and Artificial Intelligence

#artificialintelligence

Artificial intelligence has proven to be a technology that has the potential to change any industry. Chatbots are among the most popular marketing tools, and they represent only one of many areas of application of AI. Thanks to machine learning, AI can not only operate massive amounts of data but also learn from its previous experiences and improve its approaches. Given that 5G enables a much faster transfer of data, it allows developers to expand the functionality of mobile applications and to introduce new features. Let's consider the relationship between these two most promising technologies in more detail.


The State of 5G in 2020 -- Where the World and U.S. Are

#artificialintelligence

In this post, we examine the state of 5G in 2020. And while the United States is seeing good growth with this technology, it lags in average download speeds. Last year, we presented a post asking and answering: Do YOU Know What 5G Is? In March 2020, we noted that a BI Intelligence study found that "39% of respondents to our survey saying they plan to support 5G in IoT products and services before 2021." All the things we hope will make our lives easier, safer, and healthier will require high-speed, always-on internet connections.


Chinese military eying AI to gain cyber, space dominance: Japan

#artificialintelligence

The Chinese military is aiming to utilize cutting-edge technologies like private sector-developed artificial intelligence to enhance its offensive capability in domains such as cyberspace and outer space, a Japanese Defense Ministry think tank warned Friday. Beijing aspires to match the United States' overall military capacity by transforming its People's Liberation Army into a world-class fighting force with the help of advanced technologies, the National Institute for Defense Studies said in its annual report on China's security strategy. The report said that until the Chinese catch up with the American military, "the PLA will build up its interference and strike capabilities to prevent the United States' military use of both the cyber and space domains." The China Security Report 2021 was released as the rivalry between Washington and Beijing has been intensifying, as has competition for technological hegemony. The United States has restricted exports of semiconductors to Huawei Technologies Co., the Chinese telecom giant that is aiming to expand its dominance of next-generation 5G technology.


Chinese military eying AI to gain cyber, space dominance: think tank

The Japan Times

The Chinese military is aiming to utilize cutting-edge technologies like private sector-developed artificial intelligence to enhance its offensive capability in domains such as cyberspace and outer space, a Japanese Defense Ministry think tank warned Friday. Beijing aspires to match the United States' overall military capacity by transforming its People's Liberation Army into a world-class fighting force with the help of advanced technologies, the National Institute for Defense Studies said in its annual report on China's security strategy. The report said that until the Chinese catch up with the American military, "the PLA will build up its interference and strike capabilities to prevent the United States' military use of both the cyber and space domains." The China Security Report 2021 was released as the rivalry between Washington and Beijing has been intensifying, as has competition for technological hegemony. The United States has restricted exports of semiconductors to Huawei Technologies Co., the Chinese telecom giant that is aiming to expand its dominance of next-generation 5G technology.


Huawei, long resilient, suffers as U.S. ramps up pressure

The Japan Times

BEIJING – For nearly a decade, Huawei kept its worldwide sales growing even as Washington told U.S. phone companies not to buy its network equipment and lobbied allies to reject China's first global tech brand as a security threat. Focusing on Europe, Asia, Africa and China's booming market, Huawei became the biggest maker of switching gear and a major smartphone brand. As the White House cut off access to American components and Google's popular music and other smartphone services, Huawei unveiled its own processor chips and app development. Last year's sales rose 19 percent to $123 billion (¥13 trillion). But now Huawei Technologies Ltd. is suffering in earnest, as Washington intensifies a campaign to slam the door on access to foreign markets and components in its escalating feud with Beijing over technology and security.


A Framework for Behavioral Biometric Authentication using Deep Metric Learning on Mobile Devices

arXiv.org Machine Learning

Mobile authentication using behavioral biometrics has been an active area of research. Existing research relies on building machine learning classifiers to recognize an individual's unique patterns. However, these classifiers are not powerful enough to learn the discriminative features. When implemented on the mobile devices, they face new challenges from the behavioral dynamics, data privacy and side-channel leaks. To address these challenges, we present a new framework to incorporate training on battery-powered mobile devices, so private data never leaves the device and training can be flexibly scheduled to adapt the behavioral patterns at runtime. We re-formulate the classification problem into deep metric learning to improve the discriminative power and design an effective countermeasure to thwart side-channel leaks by embedding a noise signature in the sensing signals without sacrificing too much usability. The experiments demonstrate authentication accuracy over 95% on three public datasets, a sheer 15% gain from multi-class classification with less data and robustness against brute-force and side-channel attacks with 99% and 90% success, respectively. We show the feasibility of training with mobile CPUs, where training 100 epochs takes less than 10 mins and can be boosted 3-5 times with feature transfer. Finally, we profile memory, energy and computational overhead. Our results indicate that training consumes lower energy than watching videos and slightly higher energy than playing games.