IOT

arXiv:2609.28588v1 Announce Type: new Abstract: Massive Internet of Things (IoT) networks operate with short packets whose reliability is limited by finite block- length (FBL) effects, while remote deployments increasingly rely on Low Earth Orbit (LEO) satellites for backhaul connectivity that is sensitive to atmospheric attenuation. In this paper, we pro- pose a unified end-to-end framework for satellite-assisted massive IoT networks that jointly models uplink FBL random access, sensing assisted satellite backhaul, and worst user broadcast downlink transmission. Uplink reliability is characterized using stochastic geometry, while atmospheric sensing and conservative SNR margins enable FBL-safe backhaul adaptation. Numerical results reveal an optimal uplink access probability due to the tradeoff between spatial reuse and FBL reliability, and show that sensing assisted backhaul margins significantly improve robustness against attenuation uncertainty.

arXiv:2609.28725v1 Announce Type: new Abstract: Machine learning-based Network Intrusion Detection Systems often report near-perfect performance on IoT benchmarks. However, whether these models learn generalizable attack behavior or exploit spurious dataset shortcuts- such as static testbed IP/MAC addresses and chronological recording artifacts-remains an important question. We evaluate the CyberFlowIoT-GICAP benchmark, containing 3,617,388 flow records across 126 PCAP sessions with 849,395 benign flows. Four learning paradigms are evaluated across four feature configurations using PCAP-disjoint splits; LightGBM is additionally evaluated using conventional random-flow splitting. When only statistical flow behavior is used (Fbehav), LightGBM (92.58% +/- 8.18%), Random Forest (92.59% +/- 8.18%), and Deep MLP (92.55% +/- 8.18%) achieve nearly identical Macro-F1, indicating that performance is constrained by feature representation rather than model complexity. With raw timestamps

arXiv:2609.28588v1 Announce Type: new Abstract: Massive Internet of Things (IoT) networks operate with short packets whose reliability is limited by finite block- length (FBL) effects, while remote deployments increasingly rely on Low Earth Orbit (LEO) satellites for backhaul connectivity that is sensitive to atmospheric attenuation. In this paper, we pro- pose a unified end-to-end framework for satellite-assisted massive IoT networks that jointly models uplink FBL random access, sensing assisted satellite backhaul, and worst user broadcast downlink transmission. Uplink reliability is characterized using stochastic geometry, while atmospheric sensing and conservative SNR margins enable FBL-safe backhaul adaptation. Numerical results reveal an optimal uplink access probability due to the tradeoff between spatial reuse and FBL reliability, and show that sensing assisted backhaul margins significantly improve robustness against attenuation uncertainty.

The Incident In late September 2026, Samsung experienced a significant software disaster that left thousands of smart refrigerator owners in South Korea facing a nightmare scenario: their fridges completely stopped working. The incident, which occurred during a SmartThings update rollout, resulted in spoiled food, non-functional automatic door-opening features, and broken internal lighting systems. What makes this incident particularly troubling is that it appears to have been caused by a work-i...

arXiv:2609.28170v1 Announce Type: new Abstract: Zero Trust (ZT) replaces the implicit trust of perimeter-based security with explicit, continuous, context-aware authorization. This shift is particularly relevant to IoT and cyber-physical systems, whose heterogeneous, long-lived, and remotely connected components make persistent trust untenable. Yet their physical coupling complicates ZT adoption: restricting a suspicious component can reduce cyber exposure while removing telemetry or control capabilities required for operation. Existing work mainly models physical harm caused by attacks, with less attention to consequences introduced by enforcement itself. We introduce Safety-Aware Zero Trust (SA-ZT), which treats restriction-induced physical consequences as policy inputs. We map the NIST ZT tenets to nine IoT/CPS convergence strains, distinguish IoT-amplified challenges from those specific to cyber-physical coupling, and derive corresponding operational requirements. SA-ZT extends

arXiv:2609.27202v1 Announce Type: new Abstract: The growing deployment of Internet of Things (IoT) devices has increased the need for privacy-preserving intrusion detection systems that operate directly on resource-constrained hardware. Federated Learning enables collaborative model training without sharing raw data, but conventional federated models are often too large and unstable for deployment on microcontroller-class devices. TinyML techniques enable compact neural networks but are typically designed for inference-only workloads. This work investigates combining Federated Learning with TinyML-based model compression for intrusion detection in IoT environments. We evaluate compression strategies including knowledge distillation, structured pruning, and quantization within a federated training pipeline. Preliminary results show that training stability plays a critical role in federated TinyML systems. In particular, server-coordinated cosine learning-rate scheduling improves

One of the best things to buy during (or leading up to) sales events is expensive home gadgets. These Roborock robot vacuums are already on markdown.

Bloomberg: Sources: Schneider Electric is nearing a deal to acquire Bulgaria-based smart home device maker Shelly Group at a €1.27B valuation, excluding debt  —  Schneider Electric SE is nearing an agreement to acquire Shelly Group SE, a maker of smart devices for the home, according to people familiar with the matter.

Modern agriculture has quietly become one of the most data-intensive industries on the planet. Fields dotted with soil sensors, drones overhead, automated irrigation lines, and networked greenhouses generate continuous streams of telemetry that must be routed to cloud servers, analyzed, and turned into decisions within seconds. As farms scale up their digital infrastructure, the plumbing […]

Sangmi Cha / Bloomberg: Chinese chip foundry CanSemi, focused on automotive, industrial, and IoT chips, files for an IPO on Shenzhen stock exchange's ChiNext, seeking to raise ~$919M  —  Chinese chip foundry CanSemi Technology Inc. is seeking to raise about 6.16 billion yuan ($919 million) in an initial public offering …

arXiv:2609.26601v1 Announce Type: cross Abstract: Intelligent reflecting surface (IRS)-assisted mobile Internet of Things uplinks require joint control of channel aging, costly cascaded channel state information (CSI) acquisition, and coupled IRS/radio resources. This investigation develops a unified prediction-aware deterministic framework for partitioned IRS-assisted massive multiple-input multiple-output (mMIMO) uplinks. Direct channels are recursively tracked, whereas cascaded channels are selectively refreshed by differential semi-blind acquisition reusing the same unknown data block across a minimum-reflection baseline and DFT-coded IRS states. Moreover, finite-block acquisition covariances initialize reduced-order beam-domain prediction, which propagates only unit-beam means online and retrieves age-dependent covariances from precomputed tables. A mixed-integer nonconvex formulation captures net throughput, fairness, outage, uncertainty, switching cost, and sliding-window IRS

arXiv:2609.25787v1 Announce Type: new Abstract: Encryption hides IoT payloads, but traffic shape can still reveal device identity through packet sizes, timing, direction, and packetization. We present Adaptive Traffic Camouflage, a causal, leakage-aware controller that characterizes traffic-shape leakage without runtime device labels and selects a budget-feasible transformation for the next traffic window from previous-window context. The controller chooses among padding, packet splitting, timing, and composite transformations, or leaves traffic unchanged when camouflage is unnecessary. We evaluate the design on CIC-IoT-2022, IoT Sentinel, and UNSW using classical and sequence-based fingerprinting models under clean-trained, defense-aware, and incremental-exposure settings, with fixed, random, and mean-bandwidth-matched baselines. Under the Balanced profile, camouflage reduces mean Macro-F1 by 13.2-23.3% relative to clean traffic with 4.88-7.47% average bandwidth overhead and at most

Shenzhen Camsense Technologies, a maker of spatial sensors for robotic vacuum cleaners, launched a Hong Kong initial public offering (IPO) that aims to raise about HK$680 million (US$86.7 million), despite headwinds from Washington’s recent import ban on foreign-made vacuum robots. “The export and procurement for our existing client products remain normal, with potential disruption limited to new product development schedules,” Camsense co-founder Zhou Kun said about the ban’s impact. “We have...

arXiv:2609.23678v1 Announce Type: new Abstract: Remote source monitoring is a key use case for Internet of things (IoT) applications, calling on efficient communications protocols to ensure timely data delivery. In this paper, we consider a practically inspired scenario in which an IoT device reports sensor readings to a gateway over a correlated, lossy channel, receiving feedback on the transmission outcome only after some delay. For this setting, we investigate practical threshold-based reporting strategies for monitoring a Markov process, and evaluate two approaches: a reactive strategy where the node awaits feedback after an update, and a proactive strategy that preemptively transmits a second update. Leveraging Markov renewal processes, we provide an exact performance analysis in terms of the mean squared error (MSE). Our study characterizes the fundamental trade-off between estimation error and communication rate, revealing that proactive transmissions significantly improve MSE

Track occupancy and motion continuously without keeping the full sensing and processing chain active. The post How 60 GHz Radar Improves Low-Power Presence Sensing In IoT Devices appeared first on Semiconductor Engineering.

arXiv:2609.21566v1 Announce Type: new Abstract: Emerging 6G industrial IoT architectures require wireless networked control systems capable of stabilizing diverse control loops over tightly constrained radio resources. Conventional periodic and Age-of-Information (AoI) based scheduling guarantees bounded staleness at the cost of persistent channel saturation. Conversely, pure event-triggered (PureET) strategies minimize transmissions but risk catastrophic silent deterioration when local sensor-side thresholds fail to reflect critical state evolution. To bridge this gap, we propose a communication-control co-design framework governed by a 6G Semantic Layer that independently arbitrates uplink and downlink resources. Instead of relying on freshness, our architecture evaluates the actual control impact of a packet using the state-to-error ratio (SER). We unify this control confidence with channel reliability in terms of signal-to-noise ratio (SNR) to orchestrate a threshold-based sensor

arXiv:2609.21566v1 Announce Type: new Abstract: Emerging 6G industrial IoT architectures require wireless networked control systems capable of stabilizing diverse control loops over tightly constrained radio resources. Conventional periodic and Age-of-Information (AoI) based scheduling guarantees bounded staleness at the cost of persistent channel saturation. Conversely, pure event-triggered (PureET) strategies minimize transmissions but risk catastrophic silent deterioration when local sensor-side thresholds fail to reflect critical state evolution. To bridge this gap, we propose a communication-control co-design framework governed by a 6G Semantic Layer that independently arbitrates uplink and downlink resources. Instead of relying on freshness, our architecture evaluates the actual control impact of a packet using the state-to-error ratio (SER). We unify this control confidence with channel reliability in terms of signal-to-noise ratio (SNR) to orchestrate a threshold-based sensor

arXiv:2609.21344v1 Announce Type: new Abstract: For Internet of Things (IoT) devices, a secure algorithm alone is not enough: an attacker with physical access can attack the implementation directly, and its flaws are hard to fix once deployed. Large language models (LLMs) are now used to build and analyze such implementations. LLM benchmarks exist for cryptography and general cybersecurity, but none covers cryptographic engineering. In this paper, we present CESBench, 380 expert-written items across six sub-domains of cryptographic engineering security for IoT devices: side-channel, fault injection, implementation, countermeasures, evaluation, and integration. Four task types target different competences: 209 multiple-choice items test recall, 67 judgment items require a security verdict and its justification, 63 scenario items require an engineering diagnosis, and 41 code tasks are graded by 572 test cases. To validate the benchmark, 11 open-weight and proprietary LLMs answer every

arXiv:2609.19695v1 Announce Type: new Abstract: Federated learning (FL) enables privacy-preserving, on-device training across heterogeneous Internet-of-Things (IoT) deployments such as smart-city water-metering networks, where each smart meter observes a household-specific consumption time series. Under such statistical heterogeneity, the standard Federated Averaging (FedAvg) aggregation averages dissimilar local models into a single global model that may fail to capture client-specific patterns. We address this by forming client coalitions directly in the local-weight space and aggregating at the coalition level. Extending a prior weight-driven coalition-formation scheme, we model coalition formation as a Hegselmann-Krause (HK) bounded-confidence opinion-dynamics process acting on the local weights, and develop variants of the HK interaction based on Euclidean-distance and cosine-similarity confidence criteria. The framework is applied to short-term water-consumption forecasting with

arXiv:2609.18344v1 Announce Type: new Abstract: Blockchain-enabled Internet of Things (IoT) systems integrate smart contracts with embedded devices to support decentralized device management and access control. Their security therefore depends jointly on the logic of on-chain contracts and off-chain device firmware. Logic flaws in either layer can violate the same system invariants, such as unauthorized access, improper state changes, or unguarded privileged operations. Existing approaches rely on contract analysis, firmware analysis, and graph-based vulnerability detection. However, these methods typically focus on a single layer or artifact and often depend on predefined vulnerability patterns, emulation fidelity, or homogeneous representations that obscure security-relevant component roles. They also lack a unified architecture that supports different security tasks while remaining deployable on resource-constrained gateways. To address these limitations, we extend MA-HGAT into a

The Nurovi line includes three lidar-powered robovacs. But to get the model I’m most intrigued by, you’ll need a Costco membership.

Google Home is unlocking the agentic smart home — which is great, right?  The VergeYour AI agents can now control your Google Home devices  TechCrunchGoogle Home Is Going Agentic Via Integration With The MCP Standard  EngadgetGoogle Home app brings battery-efficient widget, reduces gray device tiles  9to5GoogleGoogle Home Gets 15+ Major Improvements  Droid Life

Google Home is unlocking the agentic smart home — which is great, right?  The VergeYour AI agents can now control your Google Home devices  TechCrunchGoogle Home Is Going Agentic Via Integration With The MCP Standard  EngadgetGoogle Home app brings battery-efficient widget, reduces gray device tiles  9to5GoogleGoogle Home Gets 15+ Major Improvements  Droid Life

Google Home MCP lets Antigravity, Claude, OpenClaw, & more control your smart home  9to5GoogleYour AI agents can now control your Google Home devices  TechCrunchGoogle Home is unlocking the agentic smart home — which is great, right?  The VergeGoogle Home Is Going Agentic Via Integration With The MCP Standard  EngadgetGoogle Home Gets 15+ Major Improvements  Droid Life

Google Home MCP lets Antigravity, Claude, OpenClaw, & more control your smart home  9to5GoogleYour AI agents can now control your Google Home devices  TechCrunchGoogle Home is unlocking the agentic smart home — which is great, right?  The VergeGoogle Home Is Going Agentic Via Integration With The MCP Standard  EngadgetGoogle Home Gets 15+ Major Improvements  Droid Life

Google today announced “Home MCP” to let your personal AI agent interact with your smart home devices via the Model Context Protocol. more…

Google is inviting third-party agents, including Claude and Open Claw, into Google Home. | Photo by Jennifer Pattison Tuohy / The Verge Google is opening up its smart home to AI agents, letting tools like Claude and Open Claw access and control your connected devices and analyze your home's data using the standardized Model Context Protocol. Google Home MCP is a new integration that lets third-party AI agents control and monitor your smart home and act on your behalf. It "allows any AI agents that support MCP, including Google Antigravity, Claude, Hermes or Open Claw, to securely work with all of the devices and event history in your Google Home ecosystem," Taylor Lehman, group product manager at Google Home & Nest, said in a blog post. According to Lehman, Home MCP integ … Read the full story at The Verge.

arXiv:2609.14798v1 Announce Type: new Abstract: As the Internet of Things (IoT) market continues to expand, many companion apps are being published in app stores, raising security concerns for those whose vendors have abandoned support. Even after vendors discontinue support, such applications frequently remain operational on users' mobile devices, continue to interface with users' IoT devices and collect user data without receiving security updates. This leaves known and newly discovered vulnerabilities unmitigated, increasing risks of remote exploitation, unauthorized device access, and prolonged data misuse. We define these abandoned applications as "IoT abandonware" and present the first large-scale measurement study of the security risks associated with discontinued applications. We analyze 61,500 IoT companion Android applications that had not been updated for at least two years or were no longer in service as of March 2025. From decompiled binaries, we extracted latent and

arXiv:2609.12412v1 Announce Type: new Abstract: Foundation models, including large language models, vision-language models, and time-series foundation models, are increasingly deployed on embedded and edge platforms for CPS and IoT applications, where energy, latency, and memory are as critical as task accuracy. Existing benchmarking tools evaluate model capability in isolation, reporting accuracy assuming sufficient compute, while hardware profiling tools remain platform-specific and mutually incompatible. As a result, users lack a unified workflow for making deployment decisions across heterogeneous devices. We present HoliBench, a modular benchmarking and deployment toolkit that jointly characterizes accuracy, latency, and energy across platforms from single-board computers to GPU servers. Its platform abstraction layer calibrates cross-device measurement, and the toolkit supports multiple model modalities, inference engines, concurrencies, and existing evaluation harnesses. An

An Apple Home computer could combine a Wi-Fi router, an AI-powered smart home hub, and local storage into a single device. | Photo by Amelia Holowaty Krales / The Verge John Ternus didn't mention Apple Home once during his first keynote as Apple CEO. But he did open by describing an "intelligent personal hub" that prioritizes local processing, protects your privacy, and integrates with all your other devices, apps, and services. While Ternus was talking about the iPhone - not a new smart home device - what he spelled out is exactly what I want to see Apple make: an intelligent home hub, a computer for your home. Rumors suggest Apple's first smart home hub with a screen is imminent. While that's long overdue, it's likely to be more interface than infrastructure, a device that can run your home locally but s … Read the full story at The Verge.

Every heartbeat that leaves a wearable sensor and travels across a wireless network is, in effect, a medical record in motion. A new study published in Cluster Computing argues that the way we protect that record has been fundamentally incomplete, and it offers a framework that treats privacy not as an afterthought bolted onto a […]

Fire alarms that cry wolf have long been one of the most frustrating weaknesses of smart home technology, but a new study suggests that a three-stage artificial intelligence pipeline can finally tell the difference between a burnt piece of toast and a genuine blaze. Researchers at a Chinese institution have developed a hybrid machine learning […]

I saw the iRobot Roomba Duo is action, and it's a two-in-one robot vacuum in the truest sense.

arXiv:2609.09348v1 Announce Type: new Abstract: Managing resources across IoT, edge, and cloud layers calls for continuous, context-aware decisions under constraints that rarely stay fixed. Deep reinforcement learning (DRL) handles this class of problems well, and large language models (LLMs) are increasingly used to augment DRL pipelines, yet the architectural relationship between the two is seldom made explicit. We build on Wang et al.'s taxonomy of Continuum Orchestration Systems employing DRL techniques and extend it with two further dimensions. The AI Augmentation Paradigm measures how LLMs are exploited, while the Feedback channel captures whether and through which system path the execution feedback returns to the LLM in order to close the MAPE control loop at the LLM Orchestration layer. We apply this taxonomy to six recent system architectures and find a common gap, as none combines full LLM orchestration with full agent-layer feedback in a Cloud Continuum setting. We relate

arXiv:2609.09161v1 Announce Type: new Abstract: The deployment of AI-driven Digital Twins (DTs) in large-scale Internet-of-Things (IoT) ecosystems demands continuous, high-fidelity synchronization between the physical environment and its virtual replica. Conventional approaches rely on dense sensor deployments, which introduce prohibitive costs in terms of hardware, energy, and network bandwidth. In this paper, we propose SMCC-DT, an integrated Sensing-Memory-Communication-Computation (SMCC) framework that enables sensorless monitoring of physical assets by exploiting Integrated Sensing and Communication (ISAC) waveforms at the 6G Edge. Under the SMCC-DT paradigm, a single radio signal simultaneously extracts environmental telemetry (Sensing) and delivers it to an Edge server (Communication), where a large-scale AI model is loaded into constrained memory (Memory) and executed (Computation) to update the DT state. We formulate the DT synchronization problem as a cross-layer

The Aqua20 Pro Ultra Roller X Complete can steam-clean your hard floors — but the feature comes with a number of caveats.

Berlin‘s Messe halls are usually a chaos of flashing screens and feature lists shouted over the din. Walk into Hall 3.1, Stand 101 this year and the noise drops. What greets you is not another wall of black boxes. It is a carefully lit landscape of surfaces that shift with the light, continuous lines that […] This story continues at The Next Web

The Roomba Max 875 Combo will mist your hard floors to loosen dried-on dirt and dislodge grease.

The Dubbelkisel lighting driver connects IKEA's integrated lights to the Dirigera smart home hub, and is Matter-enabled to give you even more options.

Every day, billions of Internet of Things devices quietly resolve domain names: smart cameras, routers, industrial sensors, medical monitors and household appliances all depend on the Domain Name System to reach the servers that keep them functioning. That same plumbing, however, has become one of the favorite channels of malware authors. A new study published […]

Researchers have unveiled a comprehensive new blueprint for the future of agriculture, introducing a concept called the Farming of Things (FoT) — a five-layer cyber-physical architecture that promises to transform farms into intelligent, self-regulating ecosystems where sensors, smartphones, edge servers, and cloud-hosted artificial intelligence work in seamless concert. The study, published in Smart Agricultural Technology […]

In the peri-urban farming communities that ring Niamey, the capital of Niger, climate change is not an abstract future threat but a lived, seasonal reality. Rainfall in the city has collapsed from 458.87 mm in 1997 to just 141.71 mm in 2020, and the West African Sahel is projected to warm faster than the global […]

I saw UGreen’s new AI-led NAS tech in action, and it could be a total game changer for your home.

I Went Shopping for My Ultimate Smart Home of the Future at IFA 2026  CNETIFA Berlin 2026 Live: The Biggest Announcements From Samsung, Dyson, LG and More  CNETThe best tech and gadgets announced at IFA so far  The VergeGizmodo’s Best of IFA 2026 Awards: See the Winners  GizmodoThe 5 Best Humanoid Robots Of IFA 2026  bgr.com

I Went Shopping for My Ultimate Smart Home of the Future at IFA 2026  CNETIFA Berlin 2026 Live: The Biggest Announcements From Samsung, Dyson, LG and More  CNETThe best tech and gadgets announced at IFA so far  The VergeGizmodo’s Best of IFA 2026 Awards: See the Winners  GizmodoThe 5 Best Humanoid Robots Of IFA 2026  bgr.com

Smart factories promise a world where machines, sensors, and human operators across different organizations exchange data seamlessly, allowing production lines to adapt in real time and supply chains to respond within milliseconds. But that promise carries a hidden cost: every transaction between factories—every material tracking update, every quality record, every machine-to-machine handshake—is a potential point […]

Turns out I need a lot more money than I actually have. 

This New iRobot Concept Is the Matryoshka of Robot Vacuums  gizmodo.comiRobot unveils the Roomba Duo  The VergeThis Robot Vacuum Aims to Compete With the Suction Power of a Stick Vacuum  CNETThe New Roomba Max 875 Has Me Excited About iRobot for the First Time in Years  PCMag UKiRobot's Roomba Max 875 Combo finally fixes robot vacuuming's biggest carpet problem  Reviewed

This New iRobot Concept Is the Matryoshka of Robot Vacuums  gizmodo.comiRobot unveils the Roomba Duo  The VergeThis Robot Vacuum Aims to Compete With the Suction Power of a Stick Vacuum  CNETThe New Roomba Max 875 Has Me Excited About iRobot for the First Time in Years  PCMag UKiRobot's Roomba Max 875 Combo finally fixes robot vacuuming's biggest carpet problem  Reviewed

iRobot unveils the Roomba Duo  The VergeThis New iRobot Concept Is the Matryoshka of Robot Vacuums  GizmodoThis Robot Vacuum Aims to Compete With the Suction Power of a Stick Vacuum  CNETiRobot's new flagship Roomba creates an airtight seal with your carpet — the competition should be worried  Tom's GuideiRobot's New $1,199 Roomba Max 875 Combo Is Its Most Powerful Robot Yet  Engadget

iRobot unveils the Roomba Duo  The VergeThis New iRobot Concept Is the Matryoshka of Robot Vacuums  GizmodoThis Robot Vacuum Aims to Compete With the Suction Power of a Stick Vacuum  CNETiRobot's new flagship Roomba creates an airtight seal with your carpet — the competition should be worried  Tom's GuideiRobot's New $1,199 Roomba Max 875 Combo Is Its Most Powerful Robot Yet  Engadget

iRobot's experimental Roomba Duo takes a unique approach to floor cleaning by pairing a powerful wet-dry unit with a smaller companion that can squeeze into tight spaces.

Ecovacs’ new X12S OmniCyclone targets dust mites, stubborn stains and robot-vacuum maintenance with stronger suction and a self-cleaning system.

This NAS company wants to run your local smart home  The VergeUgreen's New Smart Home Ecosystem Is Built Around Local AI Hubs  EngadgetUgreen Launches HomeAgent AI Hubs and Liquid-Cooled Qi2 Charger  MacRumorsUGREEN's new local AI NAS is the most well-thought-out smart home product I've ever used  Android CentralWould You Buy an AI Smart Home Hub for $20,000?  Gizmodo

This NAS company wants to run your local smart home  The VergeUgreen's New Smart Home Ecosystem Is Built Around Local AI Hubs  EngadgetUgreen Launches HomeAgent AI Hubs and Liquid-Cooled Qi2 Charger  MacRumorsUGREEN's new local AI NAS is the most well-thought-out smart home product I've ever used  Android CentralWould You Buy an AI Smart Home Hub for $20,000?  Gizmodo

The Roomba Duo is two robot floor cleaners in one. The original robot vacuum company showed off a concept robot at the IFA tech show in Berlin today. The Roomba Duo combines a heavy-duty floor-washing machine with a smaller, slimmer Roomba. The two floor cleaners can move around your home together, with the main unit mopping and sweeping larger floor areas and the smaller unit lowering mechanically when needed to clean tighter spaces, such as under tables or in corners. The Roomba Duo is a floor washer that carries a smaller robot vacuum with it. " data-portal-copyright=""> The Roomba Plus 757 lives on top. " data-portal-copyright=""> You can see part of the floor washing mechanism here, iRobot didn't show the underside of the robot. " data-portal-copyright=""> The robot's navigation systems are at the top, giving it a sort of face. " data-portal-copyright="">

Ugreen’s ‘HomeAgent’ is a local AI smart home ecosystem for its new line of cameras, more  9to5GoogleThis NAS company wants to run your local smart home  The VergeUgreen's New Smart Home Ecosystem Is Built Around Local AI Hubs  EngadgetUgreen Launches HomeAgent AI Hubs and Liquid-Cooled Qi2 Charger  MacRumorsUGREEN's new local AI NAS is the most well-thought-out smart home product I've ever used  Android Central

Ugreen’s ‘HomeAgent’ is a local AI smart home ecosystem for its new line of cameras, more  9to5GoogleThis NAS company wants to run your local smart home  The VergeUgreen's New Smart Home Ecosystem Is Built Around Local AI Hubs  EngadgetUgreen Launches HomeAgent AI Hubs and Liquid-Cooled Qi2 Charger  MacRumorsUGREEN's new local AI NAS is the most well-thought-out smart home product I've ever used  Android Central

The Romo 2's uses DJI's drone expertise to deliver precise navigation.

UGREEN's new local AI NAS is the most well-thought-out smart home product I've ever used  Android CentralThis NAS company wants to run your local smart home  theverge.comUgreen's New Smart Home Ecosystem Is Built Around Local AI Hubs  engadget.comUgreen’s ‘HomeAgent’ is a local AI smart home ecosystem for its new line of cameras, more  9to5GoogleUgreen HomeAgent HA100 Review – Local AI-powered NAS, NVR and Smart Home Hub  Mighty Gadget

UGREEN's new local AI NAS is the most well-thought-out smart home product I've ever used  Android CentralThis NAS company wants to run your local smart home  theverge.comUgreen's New Smart Home Ecosystem Is Built Around Local AI Hubs  engadget.comUgreen’s ‘HomeAgent’ is a local AI smart home ecosystem for its new line of cameras, more  9to5GoogleUgreen HomeAgent HA100 Review – Local AI-powered NAS, NVR and Smart Home Hub  Mighty Gadget

Improved mopping, stain removing spray and a physical privacy shutter build on Ecovac’s previous model.

Ugreen’s HomeAgent H100 Pro hub combines local storage, on-device AI, and a new voice assistant, Uliya, to run your smart home. | Photo by Jennifer Pattison Tuohy / The Verge Ugreen, known for its phone power banks, chargers, and NAS storage solutions, is moving into the smart home - in a big way. This week at the IFA tech show, the company launched its HomeAgent smart home platform that combines security camera storage, on-device AI, and smart home control in one system, managed by a voice assistant called Uliya, with the promise that everything runs locally. At the core of Ugreen's HomeAgent system is a hub that acts as the brain of your smart home, running a local-first AI (with some caveats) that you can interact with using natural language via Uliya. There are three hub configurations to choose from, each … Read the full story at The Verge.

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This UV bot is part of Dyson's new fleet of robot vacuums — could they finally restore the brand's robovac reputation?

Ugreen's New Smart Home Ecosystem Is Built Around Local AI Hubs  EngadgetUgreen’s ‘HomeAgent’ is a local AI smart home ecosystem for its new line of cameras, more  9to5GoogleUGREEN's new local AI NAS is the most well-thought-out smart home product I've ever used  Android CentralUgreen HomeAgent HA100 Review – Local AI-powered NAS, NVR and Smart Home Hub  Mighty GadgetVMH Media Founder Vikki Jones Joins UGREEN at Gillette Stadium for Major Smart Living Launch  PRLog

Ugreen's New Smart Home Ecosystem Is Built Around Local AI Hubs  EngadgetUgreen’s ‘HomeAgent’ is a local AI smart home ecosystem for its new line of cameras, more  9to5GoogleUGREEN's new local AI NAS is the most well-thought-out smart home product I've ever used  Android CentralUgreen HomeAgent HA100 Review – Local AI-powered NAS, NVR and Smart Home Hub  Mighty GadgetVMH Media Founder Vikki Jones Joins UGREEN at Gillette Stadium for Major Smart Living Launch  PRLog

arXiv:2609.03505v1 Announce Type: new Abstract: Anomaly detection in Internet of Things (IoT) networks presents unique challenges due to the diversity of devices, lack of labeled data, and domain variability across environments. In this paper, we propose a novel framework for multivariate time-series anomaly detection that leverages adversarial learning and contrastive loss within a sequence-based Variational Autoencoder (VAE) architecture. Our method enables zero-shot domain adaptation by jointly optimizing domain-invariant latent representations and semantically structured embedding spaces, without requiring labeled data or raw feature transfer. To address the heterogeneity of IoT deployments, we introduce encoder and decoder adaptor layers that align feature distributions across domains while preserving contextual semantics. Additionally, we propose a destination-based segmentation strategy to better model real-world communication structures in IoT traffic. Our framework is

Ugreen debuts its first AIoT lineup with HomeAgent, a local smart home hub that skips the cloud, plus a beefier MasterAgent MA100 for bigger AI jobs.

Ugreen might be most well-known for its chargers and device accessories, but its recent announcement might push it deeper into the smart home space. The company announced a local AI hub called the “HomeAgent,” alongside Ugreen’s new smart cameras and more. more…

Ugreen has three new hubs that run your smart home with local AI rather than the cloud. The top model runs on Nvidia's Jetson Thor platform and costs $20,000.

The latest Google Home update is fixing issues with alarms that some users were experiencing while also improving media and smart home voice controls in Google’s continued effort to address pain points in Gemini for Home. more…

Anker’s new MindBase is an AI-powered brain for your smart home  The VergeAnker Eufy At IFA 2026: New Security Cameras, Plus A Robot Vacuum And A Robot Lawnmower  EngadgetAnker Unveils MindBase With Matter 1.5 and HomeKit Secure Video Support  Homekit News and ReviewsAnker makes Matter smarthome bid with MindBase hub and NAS  AppleInsiderAnker just launched a ton of new products at IFA 2026 — including an AI-powered home hub  Tom's Guide

Anker’s new MindBase is an AI-powered brain for your smart home  The VergeAnker Eufy At IFA 2026: New Security Cameras, Plus A Robot Vacuum And A Robot Lawnmower  EngadgetAnker Unveils MindBase With Matter 1.5 and HomeKit Secure Video Support  Homekit News and ReviewsAnker makes Matter smarthome bid with MindBase hub and NAS  AppleInsiderAnker just launched a ton of new products at IFA 2026 — including an AI-powered home hub  Tom's Guide

The RockAqua P1 made its splashdown at IFA 2026 in Berlin, and we saw it first.

Security was the focus of Anker Eufy at IFA this year.

Anker's MindBase uses AI to run your smart home, and keep it safe.

The Anker MindBase offers a local solution for advanced AI processing of camera footage and is a smart home hub that supports Matter. | Image: Anker Anker is launching the Eufy MindBase, a local AI hub for its security cameras that runs an on-device, Anker-developed LLM, which the company says can process your footage without it ever leaving your home. It's also announcing a handful of other smart home security products at the IFA tech show in Berlin this week, including the TrackLight Cam S1, the S4 video doorbell, and a window camera. Pitched as the "central brain for the home," the MindBase is not just for Eufy security cameras; Anker is positioning it as a whole-home connectivity solution with on-device compute and local storage. Security is the first use case, but the company plans … Read the full story at The Verge.

iRobot has launched the $1,199 Roomba Max 875 Combo and the $899 Roomba Plus 678 Combo at IFA 2026.

Shelly’s first security camera keeps the monthly fees optional, and that alone could make it worth a look.

Robot vacuums aren’t very good at deep cleaning carpets. Roomba is about to show me how it’s fixed this problem.

arXiv:2609.00815v1 Announce Type: new Abstract: Remote laboratory systems improve accessibility in engineering education and research by enabling Internet-based interaction with physical equipment. This paper presents a modular IoT-enabled remote laboratory platform for hybrid energy system studies, combining renewable energy emulators, battery storage, and programmable loads within a three-interface architecture based on a web HMI, TIA Portal, and MATLAB/Simulink, all connected through a Talk2M VPN cloud. An industrial PLC and IoT gateway provide deterministic local control as well as secure remote access and monitoring. A hierarchical energy-management algorithm is validated by comparing local and remote executions under identical wind and irradiance profiles. The results show small differences in the energy balances of the renewable sources, battery, and load, while typical communication delays are on the order of 100 ms. Consequently, the platform supports research-grade remote

Homey’s new tactile touchscreen controller has a rotary dial for controlling lights, climate, music and more. Smart homes have gotten really good at making things really complicated. Turning on a light can involve multiple steps, compared to just flipping a switch. Homey, the Dutch-based smart home platform owned by LG, thinks it has a solution. This week it launched the Homey Portal, a touchscreen smart home controller that looks very promising, if very expensive. Preorders open today at an introductory price of $249/€249, with units shipping in December. A 2.8-inch round touchscreen device with a stainless steel dial, the Homey Portal can sit on a desk or mount to the wall and is powered by a USB-C cable. You tap the icons to control devices li … Read the full story at The Verge.

Six Labor Day smart home deals from Amazon and Best Buy that can actually make your home more useful.

More than fifteen years after the introduction of the term “Industry 4.0,” the fourth industrial revolution is no

A proof-of-concept smart waste system uses RPA-derived contextual data alongside physical sensors to support bin overflow prediction and collection planning.

arXiv:2608.27480v1 Announce Type: new Abstract: Tea plantations are vulnerable to Postelectrotermes militaris, commonly known as the Upcountry Live Wood Termite (ULWT), which can cause substantial damage when infestations remain undetected. This study proposes an IoT-enabled acoustic monitoring framework integrated with deep learning for early detection and severity assessment of ULWT infestations in tea plantations. Research Method: Audio signals were captured non-invasively from tea trunks using a high-sensitivity microphone connected to a Raspberry Pi-based IoT device, with geographic coordinates recorded for spatial tracking. After trimming, resampling, and segmentation, 2,000 ten-second samples were obtained, comprising 1,000 healthy and 1,000 infested samples, and divided into 1,600 training, 200 validation, and 200 test samples. The dataset used in this study is publicly available on Kaggle (Senevirathna et al. 2026). Fourier-derived spectrograms trained a CNN for infestation

As part of efforts to implement the second generation of Water Management System 2.0, Minister of Water Resources and Irrigation, Hani Swailem, reviewed on Monday the ministry’s efforts to develop smart water management, assess progress on the digital twin project for the Ismailia Canal and its branches, and discuss proposals to expand the project to […] The post Egypt advances smart water management through digital twin project appeared first on Egyptian Gazette.

A Taiwanese man sued his wife for having an affair using recordings from a robot vacuum to prove his case. He won, but got sued by the wife for infringing on her personal privacy and was fined the equivalent of 30% of what he earned as compensation previously.

Hive Meets Deep Learning: Hybrid AI Routing Boosts IoT Sensor Networks’ Energy Efficiency by Up to 38% The Internet of Things has a quiet addiction problem: it runs on batteries that nobody can easily replace. Billions of wireless sensor nodes — clipped to hospital patients, bolted to power-grid equipment, buried in farmland and forests — […]

Roborock's new Qrevo 2 Pro robot vacuum can leave its wet mop pads at the dock before moving onto carpet, while its dock handles much of the maintenance afterward.

arXiv:2608.26944v1 Announce Type: cross Abstract: Ambient IoT (A-IoT) devices rely on energy harvesting and duty cycling to sustain operation, thereby fundamentally changing collaborative sensing compared with traditional always-ON sensor networks. In this paper, we study the joint deployment and sensing scheduling of A-IoT devices equipped with directional sensing. We explore four solution strategies: (i) a grid deployment with static duty cycling, (ii) a centralized policy-gradient reinforcement learning (RL) approach that begins with a grid deployment and learns energy-aware device relocation and duty-cycling policies, (iii) a mixed-integer linear programming (LP) approach that couples static deployment design with duty-cycle allocation, and (iv) a hybrid LP+RL that combines optimization-based initialization with learning-based refinement. Using representative A-IoT use cases, we evaluate coverage as a function of device density, field-of-view, and maximum feasible duty cycle,

arXiv:2608.26944v1 Announce Type: new Abstract: Ambient IoT (A-IoT) devices rely on energy harvesting and duty cycling to sustain operation, thereby fundamentally changing collaborative sensing compared with traditional always-ON sensor networks. In this paper, we study the joint deployment and sensing scheduling of A-IoT devices equipped with directional sensing. We explore four solution strategies: (i) a grid deployment with static duty cycling, (ii) a centralized policy-gradient reinforcement learning (RL) approach that begins with a grid deployment and learns energy-aware device relocation and duty-cycling policies, (iii) a mixed-integer linear programming (LP) approach that couples static deployment design with duty-cycle allocation, and (iv) a hybrid LP+RL that combines optimization-based initialization with learning-based refinement. Using representative A-IoT use cases, we evaluate coverage as a function of device density, field-of-view, and maximum feasible duty cycle,

A New AI Routing System Could Keep IoT Sensor Networks Alive 53% Longer Tiny wireless sensors are becoming the nervous system of modern infrastructure, quietly measuring heart rates, electricity demand, air quality, temperature and countless other variables. Yet the networks that connect these devices face a stubborn practical limit: most sensor nodes run on small […]

Bryson DeChambeau hard launched his relationship with Mikayla Demaiter, plus hall passes, friends with benefits dilemmas, and a robot vacuum affair.

Clean water has always been a basic household need, but today’s homes ask more from every tap. Families