You'd never guess this lock is smart by looking at it, and that's my favorite part. No bulk or screen; looks like a regular lock from both sides of the door. Impressive design with the battery hidden inside the lock bolt. App is beautiful and easy to use. Best with accessories that need to be purchased separately.

--While current onboard state estimation methods are adequate for most driving and safety-related applications, they do not provide insights into the interaction between tires and road surfaces. This paper explores a novel communication concept for efficiently transmitting integrated wheel sensor data from an ESP32 microcontroller . Our proposed approach utilizes a publish-subscribe system, surpassing comparable solutions in the literature regarding data transmission volume. We tested this approach on a drum tire test rig with our prototype sensors system utilizing a diverse selection of sample frequencies between 1 Hz and 32 000 Hzto demonstrate the efficacy of our communication concept. The implemented prototype sensor showcases minimal data loss, approximately 0. 1 % of the sampled data, validating the reliability of our developed communication system. This work contributes to advancing real-time data acquisition, providing insights into optimizing integrated wheel sensor communication. A. Motivation Intelligent transportation systems rely on sensors to estimate their own state and that of surrounding objects. Traditional onboard methods, using inertial measurement units (IMUs), wheel encoders, and Global Navigation Satellite Systems (GNSS), operate at frequencies from 1 Hz to several hundred Hz, providing sufficient accuracy for trajectory reconstruction and stability control. However, these methods do not directly capture tire-road interactions. Even safety systems like an-tilock brake (ABS) and electronic stability programs (ESP) rely on conservative assumptions about forces and friction rather than real-time estimation.

Here are a few things to keep in mind when you go shopping for outdoor lights. Power: For most outdoor lighting, you need to run a cable to a power outlet, so you will want an outdoor socket. If you don't have an outdoor socket, it's usually a pretty cheap and quick job for an electrician to install a weatherproof one. Just be aware that large power adapters and awkwardly shaped plugs will not fit in outdoor sockets, so you will likely also want some kind of weatherproof box. I like the large Dri-Box ( 42) because it has plenty of space and scores an IP55 rating.

Garmin's new top running watch, the Forerunner 970, has very big shoes to fill as it attempts to replace one of the best training and race companions available. Can a built-in torch, a software revamp and voice control really make a difference? The Guardian's journalism is independent. We will earn a commission if you buy something through an affiliate link. The new top-of-the-line Forerunner takes the body of the outgoing Forerunner 965 and squeezes in a much brighter display, useful new running analytics and more of the advanced tech from Garmin's flagship adventure watch the Fenix 8. These upgrades come at a steep cost of 630 ( 750/ 750/A 1,399) – 30 more than its predecessor – placing it right at the top of the running and triathlon watch pile, although less than the 780 Fenix 8.

From Austin Powers to Subservience, sex robots have been staple features of blockbusters for decades. But the unusual devices are slowly but surely becoming more mainstream, with human-robot sex even predicted to become more common than human-human by 2050. Now, a Chinese company has unveiled its latest model - and it's one of the strangest we've seen yet. Ridmii, a company based in Dongguan City, has created a range of sex robots that can be controlled remotely. The doll syncs up to an app via Bluetooth, where the person in control can manage everything from squeezing to thrusting, and even moaning.

OK, so you have to say it with a smile, no matter what you're saying, because the shape of your mouth makes a difference.

Ready to turn your house into a smart home? Replacing your dumb bulbs with smart ones is perhaps the easiest way to start. Many smart bulbs can be screwed into existing light sockets, and they can be controlled remotely, put on schedules, change colors, and more. If you're feeling more ambitious, you can venture into smart string lights, light strips, wall and ceiling fixtures, smart lamps, and even smart lighting for the yard or other outdoor areas. Our guide to the best smart lighting can help you navigate the thicket of options, from the various smart light manufacturers (like Philips Hue, LIFX, Nanoleaf, and Wyze) to the connectivity standards (Wi-Fi, Bluetooth, Zigbee, and Matter). We'll also let you know which voice assistants (like Alexa, Apple's Siri, and Google Assistant) work with which lights. TechHive's editors and contributors have been testing smart bulbs and lighting products practically since the category was invented. We continuously test the latest smart lights, accessories, and the apps that control them.

Smart speakers have become the ultimate multitaskers for your home, combining great sound with the convenience of voice assistants like Alexa, Google Assistant and Siri. Whether you're streaming your favorite playlists, checking the weather, controlling your smart home devices or setting reminders hands free, a good smart speaker can make your day-to-day life a whole lot easier -- and more fun, too. If you're an audiophile, some models prioritize high-quality sound that can fill a room. If you're on a budget, there are plenty of affordable options that still pack in tons of features. And if you're deep into the smart home ecosystem, finding a speaker that seamlessly connects to your devices will be a game-changer. We've picked out the best smart speakers for every need, whether you're after booming bass, a sleek design or advanced voice assistant capabilities.

This paper proposes a hybrid quantum neural network (HQNN) for indoor user localization using received signal strength indicator (RSSI) values. We use publicly available RSSI datasets for indoor localization using WiFi, Bluetooth, and Zigbee to test the performance of the proposed HQNN. We also compare the performance of the HQNN with the recently proposed quantum fingerprinting-based user localization method. Our results show that the proposed HQNN performs better than the quantum fingerprinting algorithm since the HQNN has trainable parameters in the quantum circuits, whereas the quantum fingerprinting algorithm uses a fixed quantum circuit to calculate the similarity between the test data point and the fingerprint dataset. Unlike prior works, we also test the performance of the HQNN and quantum fingerprint algorithm on a real IBM quantum computer using cloud quantum computing services. Therefore, this paper examines the performance of the HQNN on noisy intermediate scale (NISQ) quantum devices using real-world RSSI localization datasets. The novelty of our approach lies in the use of simple feature maps and ansatz with fewer neurons, alongside testing on actual quantum hardware using real-world data, demonstrating practical applicability in real-world scenarios.

Non-Factoid (NF) Question Answering (QA) is challenging to evaluate due to diverse potential answers and no objective criterion. The commonly used automatic evaluation metrics like ROUGE or BERTScore cannot accurately measure semantic similarities or answers from different perspectives. Recently, Large Language Models (LLMs) have been resorted to for NFQA evaluation due to their compelling performance on various NLP tasks. Common approaches include pointwise scoring of each candidate answer and pairwise comparisons between answers. Inspired by the evolution from pointwise to pairwise to listwise in learning-to-rank methods, we propose a novel listwise NFQA evaluation approach, that utilizes LLMs to rank candidate answers in a list of reference answers sorted by descending quality. Moreover, for NF questions that do not have multi-grade or any golden answers, we leverage LLMs to generate the reference answer list of various quality to facilitate the listwise evaluation. Extensive experimental results on three NFQA datasets, i.e., ANTIQUE, the TREC-DL-NF, and WebGLM show that our method has significantly higher correlations with human annotations compared to automatic scores and common pointwise and pairwise approaches.