Eufy's SoloCam E40 eliminates a couple of pain points common to many home security cameras. Powered by a rechargeable battery, the E40 offers a wire-free installation that removes such logistical challenges as finding a convenient electrical outlet or installing entirely new electrical wiring that can make outdoor installations vexing. Secondly, it includes 8GB of onboard storage that stores about a month worth of video recordings, so you don't need to buy a cloud subscription to get the maximum security benefit from the camera. The E40 has a rectangular body similar to the EufyCam 2, enabling it to stand freely on any flat surface. It comes with a compact wall mount that screws into the back of the camera and can be affixed to a wall with the accompanying hardware.

Within electrical distribution networks, substation constraints management requires that aggregated power demand from residential users is kept within suitable bounds. Efficiency of substation constraints management can be measured as the reduction of constraints violations w.r.t. unmanaged demand. Home batteries hold the promise of enabling efficient and user-oblivious substation constraints management. Centralized control of home batteries would achieve optimal efficiency. However, it is hardly acceptable by users, since service providers (e.g., utilities or aggregators) would directly control batteries at user premises. Unfortunately, devising efficient hierarchical control strategies, thus overcoming the above problem, is far from easy. We present a novel two-layer control strategy for home batteries that avoids direct control of home devices by the service provider and at the same time yields near-optimal substation constraints management efficiency. Our simulation results on field data from 62 households in Denmark show that the substation constraints management efficiency achieved with our approach is at least 82% of the one obtained with a theoretical optimal centralized strategy.

Google is refreshing its Nest lineup with three new products and a refresh for the wired indoor Nest Cam. Among the newcomers are Google's first battery-powered Nest Cam and Doorbell, as a recent leak indicated. You'll be able to install them just about anywhere around your home, and connect them to a wired power source, if you prefer. The battery life depends on how many recorded events the devices detect and factors like the temperature and settings. Google says the Doorbell's battery will run for up to six months on a single charge, while the Nest Cam can run for up to seven months before you need to juice it up.

In recent years, the use of lithium-ion batteries has greatly expanded into products from many industrial sectors, e.g. cars, power tools or medical devices. An early prediction and robust understanding of battery faults could therefore greatly increase product quality in those fields. While current approaches for data-driven fault prediction provide good results on the exact processes they were trained on, they often lack the ability to flexibly adapt to changes, e.g. in operational or environmental parameters. Continual learning promises such flexibility, allowing for an automatic adaption of previously learnt knowledge to new tasks. Therefore, this article discusses different continual learning approaches from the group of regularization strategies, which are implemented, evaluated and compared based on a real battery wear dataset. Online elastic weight consolidation delivers the best results, but, as with all examined approaches, its performance appears to be strongly dependent on task characteristics and task sequence.

Researchers have figured out a way to rapidly recharge ultra dense batteries capable of powering flying cars, theoretically making them suitable for everyday use. The breakthrough with electric vertical take-off and landing (eVTOL) vehicles could enable the commercialisation of next-generation transport systems in the near future, according to the researchers from Penn State university who made the discovery. "I hope that the work we have done in this paper will give people a solid idea that we don't need another 20 years to finally get these vehicles," said Chao-Yang Wang, director of the Electrochemical Engine Center, Penn State. "I believe we have demonstrated that the eVTOL is commercially viable." The research was published today, 7 June, in the scientific journal Joule.

There is a growing interest in using electric vehicles (EVs) and drones for many applications. However, battery-oriented issues, including range anxiety and battery degradation, impede adoption. Battery swap stations are one alternative to reduce these concerns that allow the swap of depleted for full batteries in minutes. We consider the problem of deriving actions at a battery swap station when explicitly considering the uncertain arrival of swap demand, battery degradation, and replacement. We model the operations at a battery swap station using a finite horizon Markov Decision Process model for the stochastic scheduling, allocation, and inventory replenishment problem (SAIRP), which determines when and how many batteries are charged, discharged, and replaced over time. We present theoretical proofs for the monotonicity of the value function and monotone structure of an optimal policy for special SAIRP cases. Due to the curses of dimensionality, we develop a new monotone approximate dynamic programming (ADP) method, which intelligently initializes a value function approximation using regression. In computational tests, we demonstrate the superior performance of the new regression-based monotone ADP method as compared to exact methods and other monotone ADP methods. Further, with the tests, we deduce policy insights for drone swap stations.

If you have existing low-voltage wiring, you can take advantage of that power source--and your existing analog or digital chime--and never worry about replacing the Kami Doorbell Camera's batteries. If you don't have wiring in place, you can run this camera on battery power. Add in person detection in a camera that's currently selling on Amazon for $100 and you have a solid smart home value. Just don't buy one in anticipation of Kami delivering on its facial recognition promise, because that feature was highly unreliable in our experience. You'll also need to pay a subscription fee to unlock all of this camera's features.

The quest for new and better actuation technologies and'soft' robotics is often based on principles of biomimetics, in which machine components are designed to mimic the movement of human muscles -- and ideally, to outperform them. Despite the performance of actuators like electric motors and hydraulic pistons, their rigid form limits how they can be deployed. As robots transition to more biological forms and as people ask for more biomimetic prostheses, actuators need to evolve. Associate professor (and alum) Michael Shafer and professor Heidi Feigenbaum of Northern Arizona University's Department of Mechanical Engineering, along with graduate student researcher Diego Higueras-Ruiz, published a paper in Science Robotics presenting a new, high-performance artificial muscle technology they developed in NAU's Dynamic Active Systems Laboratory. The paper, titled "Cavatappi artificial muscles from drawing, twisting, and coiling polymer tubes," details how the new technology enables more human-like motion due to its flexibility and adaptability, but outperforms human skeletal muscle in several metrics.

Electrical batteries are increasingly crucial in a variety of applications, from integration of intermittent energy sources with demand, to unlocking carbon-free power for the transportation sector through electric vehicles (EVs), trains and ships, to a host of advanced electronics and robotic applications. A key challenge however is that batteries degrade quickly with operating conditions. It is currently difficult to estimate battery health without interrupting the operation of the battery or without going through a lengthy procedure of charge-discharge that requires specialized equipment. In work recently published by Nature Machine Intelligence, researchers from the Smart Systems Group at Heriot-Watt University in Edinburgh, UK working together with researchers from the CALCE group at the University of Maryland in the US developed a new method to estimate battery health irrespective of operating conditions and battery design or chemistry, by feeding artificial intelligence (AI) algorithms with the raw battery voltage and current operational data. Darius Roman, the Ph.D. student that designed the AI framework said: "To date, the progress of data-driven models for battery degradation relies on the development of algorithms that carry out inference faster. Whilst researchers often spend a considerable amount of time on model or algorithm development, very few people take the time to understand the engineering context in which the algorithms are applied. By contrast, our work is built from the ground up. We first understand battery degradation through collaborations with the CALCE group at the University of Maryland, where in-house degradation testing of batteries was carried out. We then concentrate on the data, where we engineer features that capture battery degradation, we select the most important features and only then we deploy the AI techniques to estimate battery health."

Sonos's new smaller and cheaper Roam portable speaker is one that won't end up relegated to a drawer collecting dust as it sounds great at home too. The £159 Roam joins the much bigger and heavier £399 Move as the second of firm's battery-powered models and proves itself as one of the best options in a saturated market. The speaker has both wifi and Bluetooth and is triangular in shape, like a Toblerone, but only about the length of a 500ml bottle. It weighs 430g so won't drag down a bag and is easy to grip for carrying about the house. The front is a metal mesh, the back is high-quality mat plastic and the end caps are rubber to help absorb impacts if you drop it.