IOT

arXiv:2501.13508v1 Announce Type: new Abstract: The safe and swift evacuation of passengers from Maritime Vessels, requires an effective Internet of Things(IoT) as well as an information and communication technology(ICT) infrastructure. However, during emergencies, delays in IoT and ICT systems that guide evacuees, can impair the evacuation process. This paper presents explores the impact of the key IoT and ICT elements. The methodology builds upon the deadline-aware adaptive navigation strategy (ANT), which offers the path segment that minimizes the evacuation time for each evacuee at each decision instant. The simulations on a real cruise ship configuration, show that delays in the delivery of correct instructions to evacuees can significantly hinder the effectiveness of the evacuation. Our findings stress the need to design robust and computationally fast IoT and ICT systems to support the evacuation of passengers in ships, and underscores the key role played by the IoT in the

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Google’s Nest Learning thermostat. | Photo by Jennifer Pattison Tuohy / The Verge Google is bringing smart home controls in Gemini to everyone. The Google Home extension in the Gemini app is adding a few new features, in addition to letting you adjust your smart lighting, thermostat, speakers, and other compatible devices as long as they’re connected to your Google account. Google first previewed the extension last November. With it, you can use natural language to control your smart home when interacting with Gemini, such as saying “The sun is too bright in the living room” to close your smart blinds. But now, Gemini can also carry out multiple requests, like “Turn the armchair light on too, but dim the kitchen lamp.” You’ll be able to use the Google Home extension to ask Gemini about the status of your devices too, such as whether you’ve left your porch light on. Additionally,

The Eureka E20 Plus is a self-emptying robot vacuum that lacks one feature found in most competitors - but that's what makes it so great.

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Here's how the Google Pixel Tablet performs better (and worse) than stationary displays like the Nest and Echo Hub.

arXiv:2501.12483v1 Announce Type: new Abstract: This study provides a framework that incorporates the Internet of Things (IoT) technology into maize farming activities in Central Uganda as a solution to various challenges including climate change, sub-optimal resource use and low crop yields. Using IoT-based modeling and simulation, the presented solution recommends cost-effective and efficient approaches to irrigation, crop yield improvement enhancement and prevention of drinking water loss while being practical for smallholder farmers. The framework is developed in a manner that is appropriate for low resource use regions by using local strategies that are easily understandable and actionable for the farmers thus solving the issue of technology access and social economic constraints. Research in this area brought to light the promise that the IoT holds for the evolution of agriculture into a more data-informed, climate-smart sector, contributes to the much-needed food in the world,

The new Home AI features will sense when you're working out or sleeping, for example, to suggest different routines for the activity. Here's how that would work.

Bigger, badder DDoSes are flooding the Internet. Dismal IoT security is largely to blame.

Los Angeles CA (SPX) Jan 22, 2025 Rocket Lab USA, Inc. has announced the upcoming launch of its Electron rocket for Kineis, a global Internet-of-Things (IoT) connectivity provider. This mission, titled "IOT 4 You and Me," is scheduled to lift off during a launch window opening on February 4th, NZDT. The daily launch opportunity within this window is at 09:43 am NZDT (20:43 UTC). The launch will take place at Rocket Lab's L

The White House launched a new cybersecurity safety label, the U.S. Cyber Trust Mark, intended to help consumers make informed decisions on smart device safety.

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arXiv:2310.08822v2 Announce Type: replace Abstract: We propose a new coded blockchain scheme suitable for the Internet-of-Things (IoT) network. In contrast to existing works for coded blockchains, especially blockchain-of-things, the proposed scheme is more realistic, practical, and secure while achieving high throughput. This is accomplished by: 1) modeling the variety of transactions using a reward model, based on which an optimization problem is solved to select transactions that are more accessible and cheaper computational-wise to be processed together; 2) a transaction-based and lightweight consensus algorithm that emphasizes on using the minimum possible number of miners for processing the transactions; and 3) employing the raptor codes with linear-time encoding and decoding which results in requiring lower storage to maintain the blockchain and having a higher throughput. We provide detailed analysis and simulation results on the proposed scheme and compare it with the

arXiv:2209.13793v2 Announce Type: replace Abstract: The concepts of Internet of Things (IoT) and Cyber Physical Systems (CPS) are closely related to each other. IoT is often used to refer to small interconnected devices like those in smart home while CPS often refers to large interconnected devices like industry machines and smart cars. In this paper, we present a unified view of IoT and CPS: from the perspective of network architecture, IoT and CPS are similar given that they are based on either the OSI model or TCP/IP model. In both IoT and CPS, networking/communication modules are attached to original things so that isolated things can be integrated into cyber space. If needed, actuators can also be integrated with a thing so as to control the thing. With this unified view, we can perform risk assessment of an IoT/CPS system from six factors, hardware, networking, operating system (OS), software, data and human. To illustrate the use of such risk analysis framework, we analyze an

arXiv:2501.12169v1 Announce Type: new Abstract: With the advancement of Internet of Things (IoT) technology, underwater target detection and tracking have become increasingly important for ocean monitoring and resource management. Existing methods often fall short in handling high-noise and low-contrast images in complex underwater environments, lacking precision and robustness. This paper introduces a novel SVGS-DSGAT model that combines GraphSage, SVAM, and DSGAT modules, enhancing feature extraction and target detection capabilities through graph neural networks and attention mechanisms. The model integrates IoT technology to facilitate real-time data collection and processing, optimizing resource allocation and model responsiveness. Experimental results demonstrate that the SVGS-DSGAT model achieves an mAP of 40.8% on the URPC 2020 dataset and 41.5% on the SeaDronesSee dataset, significantly outperforming existing mainstream models. This IoT-enhanced approach not only excels in

arXiv:2501.11984v1 Announce Type: new Abstract: Long-range frequency-hopping spread spectrum (LR-FHSS) promises to enhance network capacity by integrating frequency hopping into existing Long Range Wide Area Networks (LoRaWANs). Due to its simplicity and scalability, LR-FHSS has generated significant interest as a potential candidate for direct-to-satellite IoT (D2S-IoT) applications. This paper explores methods to improve the reliability of data transfer on the uplink (i.e., from terrestrial IoT nodes to satellite) of LR-FHSS D2S-IoT networks. Because D2S-IoT networks are expected to support large numbers of potentially uncoordinated IoT devices per satellite, acknowledgment-cum-retransmission-aided reliability mechanisms are not suitable due to their lack of scalability. We therefore leverage message-replication, wherein every application-layer message is transmitted multiple times to improve the probability of reception without the use of receiver acknowledgments. We propose two

arXiv:2501.11618v1 Announce Type: new Abstract: To address the critical need for secure IoT networks, this study presents a scalable and lightweight curriculum learning framework enhanced with Explainable AI (XAI) techniques, including LIME, to ensure transparency and adaptability. The proposed model employs novel neural network architecture utilized at every stage of Curriculum Learning to efficiently capture and focus on both short- and long-term temporal dependencies, improve learning stability, and enhance accuracy while remaining lightweight and robust against noise in sequential IoT data. Robustness is achieved through staged learning, where the model iteratively refines itself by removing low-relevance features and optimizing performance. The workflow includes edge-optimized quantization and pruning to ensure portability that could easily be deployed in the edge-IoT devices. An ensemble model incorporating Random Forest, XGBoost, and the staged learning base further enhances

arXiv:2501.11574v1 Announce Type: new Abstract: Co-existence of 5G New Radio (5G-NR) with IoT devices is considered as a promising technique to enhance the spectral usage and efficiency of future cellular networks. In this paper, a unified framework has been proposed for allocating in-band resource blocks (RBs), i.e., within a multi-cell network, to 5G-NR users in co-existence with NB-IoT and LTE-M devices. First, a benchmark (upper-bound) scheduler has been designed for joint sub-carrier (SC) and modulation and coding scheme (MCS) allocation that maximizes instantaneous throughput and fairness among users/devices, while considering synchronous RB allocation in the neighboring cells. A series of numerical simulations with realistic ICI in an urban scenario have been used to compute benchmark upper-bound solutions for characterizing performance in terms of throughput, fairness, and delay. Next, an edge learning based multi-agent deep reinforcement learning (DRL) framework has been

arXiv:2501.11250v1 Announce Type: new Abstract: Integrating Internet of Things (IoT) devices in healthcare has revolutionized patient care, offering improved monitoring, diagnostics, and treatment. However, the proliferation of these devices has also introduced significant cybersecurity challenges. This paper reviews the current landscape of cybersecurity threats targeting IoT devices in healthcare, discusses the underlying issues contributing to these vulnerabilities, and explores potential solutions. Additionally, this study offers solutions and suggestions for researchers, agencies, and security specialists to overcome these IoT in healthcare cybersecurity vulnerabilities. A comprehensive literature survey highlights the nature and frequency of cyber attacks, their impact on healthcare systems, and emerging strategies to mitigate these risks.

arXiv:2501.11198v1 Announce Type: new Abstract: Internet of Things (IoT) devices have become increasingly ubiquitous with applications not only in urban areas but remote areas as well. These devices support industries such as agriculture, forestry, and resource extraction. Due to the device location being in remote areas, satellites are frequently used to collect and deliver IoT device data to customers. As these devices become increasingly advanced and numerous, the amount of data produced has rapidly increased potentially straining the ability for radio frequency (RF) downlink capacity. Free space optical communications with their wide available bandwidths and high data rates are a potential solution, but these communication systems are highly vulnerable to weather-related disruptions. This results in certain communication opportunities being inefficient in terms of the amount of data received versus the power expended. In this paper, we propose a deep reinforcement learning (DRL)

arXiv:2501.10743v1 Announce Type: new Abstract: We study an internet of things (IoT) network where devices harvest energy from transmitter power. IoT devices use this harvested energy to operate and decode data packets. We propose a slot division scheme based on a parameter $\xi$, where the first phase is for energy harvesting (EH) and the second phase is for data transmission. We define the joint success probability (JSP) metric as the probability of the event that both the harvested energy and the received signal-to-interference ratio (SIR) exceed their respective thresholds. We provide lower and upper bounds of (JSP), as obtaining an exact JSP expression is challenging. Then, the peak age-of-information (PAoI) of data packets is determined using this framework. Higher slot intervals for EH reduce data transmission time, requiring higher link rates. In contrast, a lower EH slot interval will leave IoT devices without enough energy to decode the packets. We demonstrate that both

arXiv:2501.10547v1 Announce Type: new Abstract: We present HyperCam, an energy-efficient image classification pipeline that enables computer vision tasks onboard low-power IoT camera systems. HyperCam leverages hyperdimensional computing to perform training and inference efficiently on low-power microcontrollers. We implement a low-power wireless camera platform using off-the-shelf hardware and demonstrate that HyperCam can achieve an accuracy of 93.60%, 84.06%, 92.98%, and 72.79% for MNIST, Fashion-MNIST, Face Detection, and Face Identification tasks, respectively, while significantly outperforming other classifiers in resource efficiency. Specifically, it delivers inference latency of 0.08-0.27s while using 42.91-63.00KB flash memory and 22.25KB RAM at peak. Among other machine learning classifiers such as SVM, xgBoost, MicroNets, MobileNetV3, and MCUNetV3, HyperCam is the only classifier that achieves competitive accuracy while maintaining competitive memory footprint and inference

arXiv:2501.10514v1 Announce Type: new Abstract: Bus transit plays a vital role in urban public transportation but often struggles to provide accurate and reliable departure times. This leads to delays, passenger dissatisfaction, and decreased ridership, particularly in transit-dependent areas. A major challenge lies in the discrepancy between actual and scheduled bus departure times, which disrupts timetables and impacts overall operational efficiency. To address these challenges, this paper presents a neural network-based approach for real-time bus departure time prediction tailored for smart IoT public transit applications. We leverage AI-driven models to enhance the accuracy of bus schedules by preprocessing data, engineering relevant features, and implementing a fully connected neural network that utilizes historical departure data to predict departure times at subsequent stops. In our case study analyzing bus data from Boston, we observed an average deviation of nearly 4 minutes

arXiv:2501.10430v1 Announce Type: new Abstract: Aquaculture involves cultivating marine and freshwater organisms, with real-time monitoring of aquatic parameters being crucial in fish farming. This thesis proposes an IoT-based framework using sensors and Arduino for efficient monitoring and control of water quality. Different sensors including pH, temperature, and turbidity are placed in cultivating pond water and each of them is connected to a common microcontroller board built on an Arduino Uno. The sensors read the data from the water and store it as a CSV file in an IoT cloud named Thingspeak through the Arduino Microcontroller. In the experimental part, we collected data from 5 ponds with various sizes and environments. After getting the real-time data, we compared these with the standard reference values. As a result, we can make the decision about which ponds are satisfactory for cultivating fish and what is not. After that, we labeled the data with 11 fish categories including

arXiv:2501.10743v1 Announce Type: new Abstract: We study an internet of things (IoT) network where devices harvest energy from transmitter power. IoT devices use this harvested energy to operate and decode data packets. We propose a slot division scheme based on a parameter $\xi$, where the first phase is for energy harvesting (EH) and the second phase is for data transmission. We define the joint success probability (JSP) metric as the probability of the event that both the harvested energy and the received signal-to-interference ratio (SIR) exceed their respective thresholds. We provide lower and upper bounds of (JSP), as obtaining an exact JSP expression is challenging. Then, the peak age-of-information (PAoI) of data packets is determined using this framework. Higher slot intervals for EH reduce data transmission time, requiring higher link rates. In contrast, a lower EH slot interval will leave IoT devices without enough energy to decode the packets. We demonstrate that both

Zigbang, the operator of Korea’s leading real estate brokerage app, is expanding its portfolio with smart home appliances, releasing a digital door lock without passcodes in the global market.

I’ve previously argued that Apple Intelligence could be the biggest reason to buy an Apple smart home camera. Longer term, I think it also has the potential to create a whole new era of truly smart homes. How long it will take before we can trust Apple Intelligence to run our homes is a whole other question! There’s no arguing with the fact that there’s a long way to go before the AI tech will be more than a public beta. But the longer-term potential does excite me … more…

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If it feels like every piece of home tech is now “smart,” you’re not far off. The smart home space has grown exponentially in the past few years to include speakers, cameras, locks, lights and even kitchen appliances. There are also different voice assistants and IoT standards to consider, all of which can make it confusing (to say the least) to build your smart home ecosystem from the ground up.Allow us at Engadget to help with that. We’ve tested dozens of smart home gadgets over the years and continue to test the latest offerings to see which work well and are worth your money. We recommend, before you even dive in, to resist the urge to outfit your whole home in one go. Not only can this be quite expensive, but also we think it’s generally best to buy just one or two items first to see if you like them. You should also pick a preferred voice assistant and stick with it. If you’re at the point where you’re ready to invest in a few new IoT gadgets, below are the best smart home

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arXiv:2501.09926v1 Announce Type: new Abstract: Early detection of forest fires is crucial to minimizing the environmental and socioeconomic damage they cause. Indeed, a fire's duration directly correlates with the difficulty and cost of extinguishing it. For instance, a fire burning for 1 minute might require 1 liter of water to extinguish, while a 2-minute fire could demand 100 liters, and a 10-minute fire might necessitate 1,000 liters. On the other hand, existing fire detection systems based on novel technologies (e.g., remote sensing, PTZ cameras, UAVs) are often expensive and require human intervention, making continuous monitoring of large areas impractical. To address this challenge, this work proposes a low-cost forest fire detection system that utilizes a central gateway device with computer vision capabilities to monitor a 360{\deg} field of view for smoke at long distances. A deep reinforcement learning agent enhances surveillance by dynamically controlling the camera's

Long before the era of Bluetooth and Wi-Fi, an inventor in Michigan had rigged his house with technology that simulated much of what today's smart homes can do.

Cointelegraph Research delves into Chirp’s DePIN and how it addresses the problem of the fragmented IoT industry.

A robot vacuum can cost a pretty penny, so it's important to follow these steps and get the best performance and longest battery life possible.

arXiv:2501.09394v1 Announce Type: cross Abstract: The proliferation of Internet of Things (IoT) devices equipped with acoustic sensors necessitates robust acoustic scene classification (ASC) capabilities, even in noisy and data-limited environments. Traditional machine learning methods often struggle to generalize effectively under such conditions. To address this, we introduce Q-ASC, a novel Quantum-Inspired Acoustic Scene Classifier that leverages the power of quantum-inspired transformers. By integrating quantum concepts like superposition and entanglement, Q-ASC achieves superior feature learning and enhanced noise resilience compared to classical models. Furthermore, we introduce a Quantum Variational Autoencoder (QVAE) based data augmentation technique to mitigate the challenge of limited labeled data in IoT deployments. Extensive evaluations on the Tampere University of Technology (TUT) Acoustic Scenes 2016 benchmark dataset demonstrate that Q-ASC achieves remarkable accuracy

arXiv:2501.09216v1 Announce Type: new Abstract: Prior research yielded many techniques to mitigate software compromise for low-end Internet of Things (IoT) devices. Some of them detect software modifications via remote attestation and similar services, while others preventatively ensure software (static) integrity. However, achieving run-time (dynamic) security, e.g., control-flow integrity (CFI), remains a challenge. Control-flow attestation (CFA) is one approach that minimizes the burden on devices. However, CFA is not a real-time countermeasure against run-time attacks since it requires communication with a verifying entity. This poses significant risks if safety- or time-critical tasks have memory vulnerabilities. To address this issue, we construct EILID - a hybrid architecture that ensures software execution integrity by actively monitoring control-flow violations on low-end devices. EILID is built atop CASU, a prevention-based (i.e., active) hybrid Root-of-Trust (RoT) that

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The Roborock Saros Z70 is making waves in the robot vacuum world, and its robotic arm is poised to bring added versatility to your home. Here's why I'm excited.

arXiv:2501.08990v1 Announce Type: new Abstract: Ambient internet of things (A-IoT) paradigm is under study in 3GPP with the intention to provide a sustainable solution for the IoT market without any need to replace the batteries and operate in harsh environments where it is difficult to replenish batteries. This article provides insight on 3rd Generation Partnership Project (3GPP) discussions in Release 18 and 19 with the focus on network architecture aspects. 3GPP has recently decided to start normative work in its Radio Access Network (RAN) Working Group (WG) and discussions are ongoing to start a work item in other WGs with more focus on architecture aspects. We explore and analyze various aspects of system design related to architecture requirements to support A-IoT service, different architecture options to consider, security and authentication mechanisms for A-IoT devices as well as key challenges for standardization of A-IoT service.

arXiv:2501.08840v1 Announce Type: new Abstract: Binary Static Code Analysis (BSCA) is a pivotal area in software vulnerability research, focusing on the precise localization of vulnerabilities within binary executables. Despite advancements in BSCA techniques, there is a notable scarcity of comprehensive and readily usable vulnerability datasets tailored for diverse environments such as IoT, UEFI, and MCU firmware. To address this gap, we present CveBinarySheet, a meticulously curated database containing 1033 CVE entries spanning from 1999 to 2024. Our dataset encompasses 16 essential third-party components, including busybox and curl, and supports five CPU architectures: x86-64, i386, MIPS, ARMv7, and RISC-V64. Each precompiled binary is available at two compiler optimization levels (O0 and O3), facilitating comprehensive vulnerability analysis under different compilation scenarios. By providing detailed metadata and diverse binary samples, CveBinarySheet aims to accelerate the

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Are you a frequent user of the Google Home app? Two new features are rolling out now to upgrade your smart home in a couple of key ways.

arXiv:2501.08229v1 Announce Type: new Abstract: This research proposes a system as a solution for the challenges faced by Sri Lanka' s historic railway system, such as scheduling delays, overcrowding, manual ticketing, and management inefficiencies. It proposes a multi-subsystem approach, incorporating GPS tracking, RFID-based e-ticketing, seat reservation, and vision-based people counting. The GPS based real time train tracking system performs accurately within 24 meters, with the MQTT protocol showing twice the speed of the HTTP-based system. All subsystems use the MQTT protocol to enhance efficiency, reliability, and passenger experience. The study's data and methodology demonstrate the effectiveness of these innovations in improving scheduling, passenger flow, and overall system performance, offering promising solutions for modernizing Sri Lanka's railway infrastructure.

arXiv:2501.07895v1 Announce Type: new Abstract: This paper highlights the significance of resource-constrained Internet of Things (RCD-IoT) systems in addressing the challenges faced by industries with limited resources. This paper presents an energy-efficient solution for industries to monitor and control their utilities remotely. Integrating intelligent sensors and IoT technologies, the proposed RCD-IoT system aims to revolutionize industrial monitoring and control processes, enabling efficient utilization of resources.The proposed system utilized the IEEE 802.15.4 WiFi Protocol for seamless data exchange between Sensor Nodes. This seamless exchange of information was analyzed through Packet Tracer. The system was equipped with a prototyped, depicting analytical chemical process to analyze the significant performance metrics. System achieved average Round trip time (RTT) of just 12ms outperforming the already existing solutions presented even with higher Quality of Service (QoS)

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There are flashy smart home tools headed to store shelves this year, but those might not be the products that make the biggest splash in 2025.

A cutting-edge AI tool can now predict how well seed potatoes will grow into healthy potato plants. Developed by biologists from Utrecht University in collaboration with the Delft University of Technology and plant breeders, the tool uses DNA data from bacteria and fungi found on seed potatoes and drone images of potato fields. "This marks the beginning of a new era in farming, where microbiology and AI come together to enhance agriculture."

Is the enormous Echo Show 21 Amazon's best smart display or its biggest missed opportunity? Here's my verdict.

arXiv:2501.07154v1 Announce Type: new Abstract: Data from Internet of Things (IoT) sensors has emerged as a key contributor to decision-making processes in various domains. However, the quality of the data is crucial to the effectiveness of applications built on it, and assessment of the data quality is heavily context-dependent. Further, preserving the privacy of the data during quality assessment is critical in domains where sensitive data is prevalent. This paper proposes a novel framework for automated, objective, and privacy-preserving data quality assessment of time-series data from IoT sensors deployed in smart cities. We leverage custom, autonomously computable metrics that parameterise the temporal performance and adherence to a declarative schema document to achieve objectivity. Additionally, we utilise a trusted execution environment to create a "data-blind" model that ensures individual privacy, eliminates assessee bias, and enhances adaptability across data types. This

arXiv:2501.07326v1 Announce Type: new Abstract: There is an expectation that users of home IoT devices will be able to secure those devices, but they may lack information about what they need to do. In February 2022, we launched a web service that scans users' IoT devices to determine how secure they are. The service aims to diagnose and remediate vulnerabilities and malware infections of IoT devices of Japanese users. This paper reports on findings from operating this service drawn from three studies: (1) the engagement of 114,747 users between February, 2022 - May, 2024; (2) a large-scale evaluation survey among service users (n=4,103), and; (3) an investigation and targeted survey (n=90) around the remediation actions of users of non-secure devices. During the operation, we notified 417 (0.36%) users that one or more of their devices were detected as vulnerable, and 171 (0.15%) users that one of their devices was infected with malware. The service found no issues for 99% of users.

arXiv:2501.07154v1 Announce Type: new Abstract: Data from Internet of Things (IoT) sensors has emerged as a key contributor to decision-making processes in various domains. However, the quality of the data is crucial to the effectiveness of applications built on it, and assessment of the data quality is heavily context-dependent. Further, preserving the privacy of the data during quality assessment is critical in domains where sensitive data is prevalent. This paper proposes a novel framework for automated, objective, and privacy-preserving data quality assessment of time-series data from IoT sensors deployed in smart cities. We leverage custom, autonomously computable metrics that parameterise the temporal performance and adherence to a declarative schema document to achieve objectivity. Additionally, we utilise a trusted execution environment to create a "data-blind" model that ensures individual privacy, eliminates assessee bias, and enhances adaptability across data types. This

arXiv:2501.07039v1 Announce Type: new Abstract: The Internet of Things (IoT) and mobile technology have significantly transformed healthcare by enabling real-time monitoring and diagnosis of patients. Recognizing medical-related human activities (MRHA) is pivotal for healthcare systems, particularly for identifying actions that are critical to patient well-being. However, challenges such as high computational demands, low accuracy, and limited adaptability persist in Human Motion Recognition (HMR). While some studies have integrated HMR with IoT for real-time healthcare applications, limited research has focused on recognizing MRHA as essential for effective patient monitoring. This study proposes a novel HMR method for MRHA detection, leveraging multi-stage deep learning techniques integrated with IoT. The approach employs EfficientNet to extract optimized spatial features from skeleton frame sequences using seven Mobile Inverted Bottleneck Convolutions (MBConv) blocks, followed by

arXiv:2501.06464v1 Announce Type: new Abstract: An expansion of Internet of Things (IoTs) has led to significant challenges in wireless data harvesting, dissemination, and energy management due to the massive volumes of data generated by IoT devices. These challenges are exacerbated by data redundancy arising from spatial and temporal correlations. To address these issues, this paper proposes a novel data-driven collaborative beamforming (CB)-based communication framework for IoT networks. Specifically, the framework integrates CB with an overlap-based multi-hop routing protocol (OMRP) to enhance data transmission efficiency while mitigating energy consumption and addressing hot spot issues in remotely deployed IoT networks. Based on the data aggregation to a specific node by OMRP, we formulate a node selection problem for the CB stage, with the objective of optimizing uplink transmission energy consumption. Given the complexity of the problem, we introduce a softmax-based proximal

Apple plans iPhone revamp, push into smart home, catching up with AI: report  Seeking AlphaApple’s 2025 Plan: iPhone Overhaul, Smart Home Push and AI Catch-Up  BloombergApple’s packed 2025 iPhone and iPad roadmap has just leaked  TechRadarApple's roadmap for 2025: Bloomberg analyst names Apple Watch SE redesign, iPhone Air, M4 Mac Studio and more  Notebookcheck.netApple's 2025 product roadmap: an insider's glimpse into what's in store this year  PhoneArena

Apple plans iPhone revamp, push into smart home, catching up with AI: report  Seeking AlphaApple’s 2025 Plan: iPhone Overhaul, Smart Home Push and AI Catch-Up  BloombergApple’s packed 2025 iPhone and iPad roadmap has just leaked  TechRadarApple's roadmap for 2025: Bloomberg analyst names Apple Watch SE redesign, iPhone Air, M4 Mac Studio and more  Notebookcheck.netApple's 2025 product roadmap: an insider's glimpse into what's in store this year  PhoneArena

iRobot shares drop after revealing preliminary Q4 results, with projected revenue of $171 million and expected GAAP operating loss of $59 million. read more

arXiv:2501.06033v1 Announce Type: new Abstract: As the Internet of Things (IoT) becomes more embedded within our daily lives, there is growing concern about the risk `smart' devices pose to network security. To address this, one avenue of research has focused on automated IoT device identification. Research has however largely neglected the identification of IoT device firmware versions. There is strong evidence that IoT security relies on devices being on the latest version patched for known vulnerabilities. Identifying when a device has updated (has changed version) or not (is on a stable version) is therefore useful for IoT security. Version identification involves challenges beyond those for identifying the model, type, and manufacturer of IoT devices, and traditional machine learning algorithms are ill-suited for effective version identification due to being limited by the availability of data for training. In this paper, we introduce an effective technique for identifying IoT

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Hyve showed up to CES with a mission: Create a delivery box that's both useful and package theft-proof.

According to Bloomberg’s Mark Gurman, the new Apple smart home hub, which some refer to as ‘Apple command center’ or simply ‘HomePad’, might ship a little bit later than anticipated. more…

The Roborock Saros Z70 robot vacuum, unveiled at CES 2025, features an arm that grabs toys, socks, and other small obstacles to clean your floors more thoroughly.

LAS VEGAS - Korean mid-sized agriculture machinery firm Daedong is seeking to expand its presence in the global marketplace, showcasing its artificial intelligence (AI)-powered tractors, AI plant box and other agricultural machinery at CES 2025 in Las Vegas.

CES just proved that robot vacuums can do more than clean your floors.

When it comes to smart home lighting, you have two main options: smart lightbulbs or smart outlet adapters paired with traditional lamps. Both have their place, but for me, smart bulbs offer more flexibility and control. Unlike outlet adapters, which toggle power on and off, smart bulbs give you control over brightness, color, and even dynamic scenes. If you want to take the next step in building your smart home in 2025, a set of Matter-compatible lightbulbs might be the perfect place to start. This week, I am looking at the . more…

You’ll only need to empty the Yeedi Cube’s base every once in a while. It handles the rest. | Photo by Jennifer Pattison Tuohy / The Verge The Yeedi Cube doesn’t have the modularity and extremities of some of the cool new robot vacuums we’ve seen at CES 2025, but the self-emptying, self-cleaning mopping robovac is also much more reasonably priced. It’s even cheaper today at Amazon, where you can buy it for $299.99 ($260 off) when you clip an on-page coupon. That’s the lowest price we’ve seen yet on the budget robovac. The Yeedi Cube can capably map and remember several rooms, including designated no-clean zones that you can set within the mobile app. While it doesn’t have AI-powered obstacle avoidance like some of the pricier robots we test, we found its laser-based navigation system works well enough to traverse floors that don’t have laundry, clothes, or pet waste

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The Ecovacs Deebot X8 Pro Omni uses a new roller mopping system that continuously cleans itself while also tackling tough stains.

We're giving this robot with mechanical task arm a Best of CES Award. The only question left is, how soon can we get one?

At CES 2025, Dreame introduced its premium X50 Ultra, which aspires to go where no robot vac has gone before.

What's included in the new specification and what it's important. The post Matter 1.4’s Advancements In The Smart Home appeared first on Semiconductor Engineering.

Smart gardens have come a long way in a short time, and the PlantaForm Indoor Smart Garden is one of the best implementations of the technology we've seen.

Robot vacuums are getting some outstanding upgrades this year, and ZDNET has picked the best ones of them all.

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More attention, openness, and cross-market application of tools and techniques is starting to have an impact The post Edge And IoT Security Turning A Corner appeared first on Semiconductor Engineering.

We recently published a list of 10 Best Home Appliance Stocks to Buy According to Analysts. In this article, we are going to take a look at where iRobot Corporation (NASDAQ:IRBT) stands against other best home appliance stocks to buy according to analysts. Overview of the US Home Appliance Industry The home appliance industry is […]

Whether they're futuristic concepts or jaw-dropping products you'll be able to buy this year, these are our top finds from the biggest tech show in the US.

Robot vacuums are having a very weird year at CES 2025. We’ve seen robot vacs that can scoot over stairs and pick up socks. Now, another robot vacuum maker is showing off robot vacuums that can zoom around with air purifiers, tablet stands, security cameras, tabletops and other objects on top. The SwitchBot K20+ Pro is a robot vacuum that doubles as a modular platform for other household devices. The company describes it as a “multitasking” household assistant that can perform a bunch of tasks while maybe also cleaning your floor. The vacuum itself mostly resembles a typical robot vac, if a bit larger. It also has a connector on top that supports a wide array of attachments or even appliances. The company says it can support up to 8 kg — nearly 18 lbs — and will connect seamlessly to other SwitchBot appliances like an air purifier or home security cam. The SwitchBot vac can then be programmed to follow you around or stay in one spot. Karissa Bell

Whether they're futuristic concepts or jaw-dropping products you'll be able to buy this year, here are our top finds from the biggest tech show in the US.

Smart home tech is one of the main events at CES and we've gathered the best you can find at the showcase.

arXiv:2501.03601v1 Announce Type: new Abstract: With the increasing number of connected devices and complex networks involved, current domain-specific security techniques become inadequate for diverse large-scale Internet of Things (IoT) systems applications. While cross-domain authentication and authorization brings lots of security improvement, it creates new challenges of efficiency and security. Zero trust architecture (ZTA), an emerging network security architecture, offers a more granular and robust security environment for IoT systems. However, extensive cross-domain data exchange in ZTA can cause reduced authentication and authorization efficiency and data privacy concerns. Therefore, in this paper, we propose a dynamic authentication and granularized authorization scheme based on ZTA integrated with decentralized federated learning (DFL) for cross-domain IoT networks. Specifically, device requests in the cross-domain process are continuously monitored and evaluated, and only

arXiv:2501.03577v1 Announce Type: new Abstract: Wireless Fidelity (Wi-Fi) communication technologies hold significant potential for realizing the Industrial Internet of Things (IIoT). In this paper, both Single-Input Single-Output (SISO) and polarized Multiple-Input Multiple-Output (MIMO) channel measurements are conducted in an IIoT scenario at the less congested Wi-Fi band, i.e., 5.5~GHz. The purpose is to investigate wireless characteristics of communications between access points and terminals mounted on automated guided vehicles as well as those surrounding manufacturing areas. For SISO channel measurements, statistical properties including the delay Power Spectral Density (PSD), path loss, shadowing fading, delay spread, excess delay, K-factor, and amplitude distribution of small-scale fading are analyzed and compared with those observed in an office scenario. For MIMO channel measurements, results show that there are multiple Dense Multipath Component (DMC) processes in the

CES 2025 will set the pace for smart home gadgets this year, and boy has it delivered some of the coolest smart home tech I've ever seen.

Whether they're jaw-dropping products coming in 2025 or futuristic concepts, here are our top finds from the biggest tech show in the US.

Savant wants to save you tens of thousands of dollars in home utility upgrades with its Smart Budget system.

It turns out that Roborock isn’t the only company that brought a robot vacuum with a mechanical arm to CES 2025. Rival company Dreame, which unveiled its stair-climbing robot vacuum earlier in the week, is also working on a robot vacuum with an arm for picking up objects. The device is still a prototype, according to the company, but the as yet unnamed robo vac was on full display at Dreame’s CES booth. Considering it’s still a prototype, the actual arm looked far more substantial compared to the one on Roborock’s Saros Z70. It was much thicker and had a bigger “claw” that looked like it might be able to pick up slightly heavier objects. (Roborock says its vac can pick up object that weigh up to 300 grams.)  Plot Twist: Dreame also brought a robo vac with an retractable arm to CES pic.twitter.com/dLPGC135k5 — Karissa Bell (@karissabe) January 8, 2025 Unfortunately, Dreame wasn’t showing it actually grab anything, but I was able to watch the

The Dreame X50 Ultra robot vacuum can't quite climb stairs, but it gets a lot closer than anything before it.

This indoor smart garden is giving us San Francisco vibes at CES 2025. We watched how Plantaform uses "fogponics" to grow fresh veggies and herbs indoors year-round.

The X50 Ultra robot vacuum from Dreame has two little legs it can deploy to clear some small obstacles.

Roborock's new intelligent robot doesn't just mop and vacuum... it tidies up.

Smart home devices are getting a lot smarter, thanks to improvements in standards like what Matter has introduced to the industry. To facilitate that, Google and MediaTek are partnering up to introduce a new Filogic chip dedicated to smart home products. more…

A new program from the FCC should make it easier to find devices you can trust.

This impressive vacuum cleaner with a 100-day bin capacity usually costs $729, but it can be yours today for only $200.

Cath Virginia / The Verge | Photo from Getty Images Consumers shopping for new smart home devices will soon be able to look for the an official stamp of trust from the US government: the US Cyber Trust Mark. Similar to how an Energy Star label on home appliances denotes a certain level of energy efficiency, the Cyber Trust Mark is meant to be a way for consumers to quickly understand that a connected device meets certain standards to secure it from cybersecurity threats. The standards cover things like whether a device issues software updates, how it securely moves data to the cloud, and how other devices are able to gain access to the product. Image: Federal Communications Commission Companies can voluntarily apply to use the logo by having their products tested by an accredited lab recognized by the Federal Communications Commission, showing that they

The Narwal Flow features both a clean and dirty water tank, allowing the robot to clean its mop while it's actively cleaning your floors.

The company just debuted a four-layer filtering pet water fountain that is rechargeable, quiet, and lasts up to 20 days.

The K20+ Pro does everything you want a robot vacuum to do, plus several more things you don't.

It's a smart switch that also supports gesture controls

Samsung says its home robot, Ballie, will roll out the first half of 2025  TechCrunchCES 2025: Samsung's AI Robot Ball With a Projector Is Real and Ready to Roll in 2025  CNETSamsung’s Ballie robot companion still comes in yellow, but has more AI and a promised 2025 launch  TechRadarSamsung claims its Ballie AI robot will actually be released this year  The VergeThe cute Samsung Ballie home robot will actually go on sale this year  Engadget

Samsung says its home robot, Ballie, will roll out the first half of 2025  TechCrunchCES 2025: Samsung's AI Robot Ball With a Projector Is Real and Ready to Roll in 2025  CNETSamsung’s Ballie robot companion still comes in yellow, but has more AI and a promised 2025 launch  TechRadarSamsung claims its Ballie AI robot will actually be released this year  The VergeThe cute Samsung Ballie home robot will actually go on sale this year  Engadget