Artificial Intelligence of Things (AIoT) refers to the deliberate pairing of artificial intelligence with the sensing and connectivity that the Internet of Things (IoT) already provides, so that the data streaming in from distributed devices turns into insight and, ultimately, action [1]. A properly designed AIoT syste...
Abijai M P, Riya Jyothish, L. C. Manikandan· Zenodo (CERN European Organi...· 0 citations
Artificial Intelligence of Things (AIoT) refers to the deliberate pairing of artificial intelligence with the sensing and connectivity that the Internet of Things (IoT) already provides, so that the data streaming in from distributed devices turns into insight and, ultimately, action [1]. A properly designed AIoT syste...
Abijai M P, Riya Jyothish, L. C. Manikandan· Zenodo (CERN European Organi...· 0 citations
The fraud of money laundering costs the global financial system USD 800 billion to USD 2 trillion annually, while digital banking contributes to the increasing number and complexity of money laundering transactions. If there are adversarial forces that are constantly adapting their approach to avoid complying with a co...
Tanvir Sajid, Sajida Hafeez· Future Business Journal· 0 citations
FedCKA is proposed, a Centered Kernel Alignment (CKA)-based strategy that dynamically handles the personalization-globalization trade-off, and outperforms established federated baselines, including FedBN, FedRep, and FedSelect, improving average NDS by 7 percentage points over the strongest baseline.
Jolle Verhoog, Ali Burak Ünal, H. Caesar· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
This paper aims to examine the synergistic integration of Cyber-Physical Systems (CPS) and Machine Learning (ML) as a foundational enabler for Industry 5.0, focusing on creating human-centric, sustainable and resilient manufacturing ecosystems.
The study utilizes a synthesis and review approach, analyzing re...
Venkatesh Naik, Soma Das, M. N. Vinay et al.· International Journal of Int...· 0 citations
Federated learning (FL) can support collaborative smart-grid monitoring without centralizing raw telemetry, but its value relative to local and centralized learning depends on both the operating regime and the learning model. This study evaluates that hypothesis in a physics-based AC power-flow simulation framework bui...
Tymoteusz I. Miller, Irmina Durlik· Electronics· 0 citations
Federated learning with blockchain technology is a promising domains to facilitate privacy-sensitive collaborative intelligence in the domain of medical imaging. Traditional federated learning systems are affected by several classes of vulnerabilities, including dependence on a single aggregator, susceptibility to gr...
A. Yadav· Engineering Research Express· 0 citations
Federated Learning (FL) enables collaborative intrusion detection across distributed Internet of Things (IoT) edge devices without centralizing private network telemetry. However, existing frameworks assume static data distributions and fail under non-stationary conditions: emerging zero-day attack families cause sever...
AlHayan Abdullah· Zenodo (CERN European Organi...· 0 citations
Digital technologies are reshaping companion-animal healthcare by expanding access to veterinary services and enabling more connected, data-driven models of care. This narrative review synthesizes current evidence on digital veterinary care, with a focus on the integration of telemedicine, artificial intelligence (AI),...
M. A. Islam, Md. Khalid Hasan Sumon, Jesmin Sultana et al.· International Symposium on P...· 0 citations
The rapid evolution of decentralized finance (DeFi) has ushered in transformative
opportunities for global financial inclusion, digital asset management, and permissionless
transactions. However, the growth of DeFi also presents significant challenges related to data
integrity, security, scalability, and regulatory com...
Damodar Bihani· WORLD JOURNAL OF INNOVATION...· 5 citations
Air pollution is a major global environmental and public health challenge, causing respiratory diseases, environmental degradation, and premature mortality. Accurate air quality prediction is essential for environmental management, reducing human exposure to harmful pollutants, and supporting timely mitigation strategi...
Thomas Jeremiah Mwabobo, Ling Qi, Ahsan Raza· East African Journal of Info...· 0 citations
The COVID-19 pandemic accelerated the development of artificial intelligence (AI), machine learning (ML), and deep learning (DL) for clinical decision support, public-health surveillance, and pandemic response. This systematic review evaluates AI-based studies addressing COVID-19 diagnosis, prognosis, outbreak forecast...
Mahdee Jodayree, Arman Kavoosi Ghafi, Issa Khodadadi et al.· Applied Network Science· 0 citations
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
MIT News · Artificial Intelligence· news.mit.eduOct 13, 2026
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
