Samsung Wallet, Aliro Locks, and SmartThings turn a simple tap into total home control

What if getting into your home didn’t require fumbling for keys, digging through bags, or wondering whether you locked the door on your way out? With the Samsung Wallet, SmartThings, and Aliro-certified smart locks from trusted brands like Aqara, Nuki, ULTRALOQ, and Schlage, your Galaxy phone can become your new door key, unlocking a smarter, safer, and more convenient home experience.

Now available on Samsung.com, Aliro-certified locks integrate with SmartThings and Samsung Wallet, giving you tap-to-unlock access, remote control, and powerful home automations that start the moment you walk through the door.

Tap to Unlock. Walk Right In.

Ever arrive home from a run with nowhere to stash your keys?

Instead of slowing down, soon you can simply tap your Galaxy phone on your smart lock. The door unlocks instantly, no physical keys required. Samsung Wallet securely stores your digital keys, while SmartThings keeps everything connected behind the scenes. It’s a simple gesture that makes everyday routines feel effortless.

Unlocking your door can trigger far more than just entry. When paired with SmartThings and a compatible hub, Aliro-certified smart locks can become the starting point for your entire home:

• Lights turn on as you step inside
• Thermostat adjusts to your preferred temperature
• Security cameras shift modes
• Alarms disarm and re-arm automatically

Heading out? Lock the door from your phone when you leave, and SmartThings takes care of the rest, shutting off lights or securing devices so you can leave with peace of mind.

Designed for Real-Life Moments

Technology should make life easier, especially in the moments that matter most.

Active lifestyles: Going for a run or walking the dog? Leave your keys behind. Your Galaxy has you covered.

Locked-out scares: Step outside to take out the trash and hear the door click shut? No panic required, tap your phone and get back in.

Family members: Share secure digital keys with family members through Samsung Wallet, and use SmartThings to manage alarms and routines while they’re inside. Members added to SmartThings can use a designated PIN as well to use the features. 

Built for What’s Next: Aliro-Certified Smart Locks

Samsung’s tap-to-unlock experience is powered by Aliro Home Key certification, an industry standard created to make digital access to your home more secure, reliable, and interoperable across devices.

Aliro-certified smart locks will work seamlessly with Galaxy phones through Samsung Wallet, delivering consistent tap-to-unlock access whether you’re coming home from work, heading out for a run, or letting in a guest remotely.

And this ecosystem is growing.

Samsung is partnering with a broad range of Aliro-certified lock makers, including Aqara, Nuki, and Allegion brands like Schlage, giving homeowners more flexibility and choice when upgrading their front door.

That means confidence today and peace of mind that your home is ready for what comes next.

How to Set Up an Aliro-Certified Lock with Galaxy

Getting started is easier than you might think.

Step 1: Install Your Aliro-Certified Lock

• Follow the manufacturer’s instructions to physically install your lock.

Step 2: Add the Lock in the SmartThings App

• Open the SmartThings app.
• Tap Add device and follow the on-screen prompts to connect your lock.

Step 3: Add Your Digital Key to Samsung Wallet

• Once connected, you’ll receive the option to add your home key to Samsung Wallet.
• Confirm and authenticate, your Galaxy phone is now your key.

Step 4: Test Tap-to-Unlock

• Hold your Galaxy phone near the lock.
• Tap. Unlock. Done.

Want a Routine to try? Try This!

Routine Name: “I’m Home!”

Trigger: When front door unlocks

Actions:

• Turn on entryway and living room lights
• Adjust thermostat to comfort setting
• Disarm security system
• Turn on Samsung TV Plus automatically 

Now your home responds automatically the moment you walk in.

You can customize this routine for mornings, evenings, guests, or even specific users.

Ready to upgrade? Shop the Aliro-compatible smart locks, Galaxy Devices, and SmartThings hubs now on Samsung.com and fully unlock your home’s potential.

The electricity to an island goes out. To find the break in the underwater power cable, a ship pulls up the entire line or deploys remotely operated vehicles (ROVs) to traverse the line. But what if an autonomous underwater vehicle (AUV) could map the line and pinpoint the location of the fault for a diver to fix?

Such underwater human-robot teaming is the focus of an MIT Lincoln Laboratory project funded through an internally administered R&D portfolio on autonomous systems and carried out by the Advanced Undersea Systems and Technology Group. The project seeks to leverage the respective strengths of humans and robots to optimize maritime missions for the U.S. military, including critical infrastructure inspection and repair, search and rescue, harbor entry, and countermine operations.

“Divers and AUVs generally don’t team at all underwater,” says principal investigator Madeline Miller. “Underwater missions requiring humans typically do so because they involve some sort of manipulation a robot can’t do, like repairing infrastructure or deactivating a mine. Even ROVs are challenging to work with underwater in very skilled manipulation tasks because the manipulators themselves aren’t agile enough.”

Beyond their superior dexterity, humans excel at recognizing objects underwater. But humans working underwater can’t perform complex computations or move very quickly, especially if they are carrying heavy equipment; robots have an edge over humans in processing power, high-speed mobility, and endurance. To combine these strengths, Miller and her team are developing hardware and algorithms for underwater navigation and perception — two key capabilities for effective human-robot teaming.

As Miller explains, divers may only have a compass and fin-kick counts to guide them. With few landmarks and potentially murky conditions caused by a lack of light at depth or the presence of biological matter in the water column, they can easily become disoriented and lost. For robots to help divers navigate, they need to perceive their environment. However, in the presence of darkness and turbidity, optical sensors (cameras) cannot generate images, while acoustic sensors (sonar) generate images that lack color and only show the shapes and shadows of objects in the scene. The historical lack of large, labeled sonar image datasets has hindered training of underwater perception algorithms. Even if data were available, the dynamic ocean can obscure the true nature of objects, confusing artificial intelligence. For instance, a downed aircraft broken into multiple pieces, or a tire covered in an overgrowth of mussels, may no longer resemble an aircraft or tire, respectively.

“Ultimately, we want to devise solutions for navigation and perception in expeditionary environments,” Miller says. “For the missions we’re thinking about, there is limited or no opportunity to map out the area in advance. For the harbor entry mission, maybe you have a satellite map but no underwater map, for example.”

On the navigation side, Miller’s team picked up on work started by the MIT Marine Robotics Group, led by John Leonard, to develop diver-AUV teaming algorithms. With their navigation algorithms, Leonard’s group ran simulations under optimal conditions and performed field testing in calm waters using human-paddled kayaks as proxies for both divers and AUVs. Miller’s team then integrated these algorithms into a mission-relevant AUV and began testing them under more realistic ocean conditions, initially with a support boat acting as a diver surrogate, and then with actual divers.

“We quickly learned that you need more sensing capabilities on the diver when you factor in ocean currents,” Miller explains. “With the algorithms demonstrated by MIT, the vehicle only needed to calculate the distance, or range, to the diver at regular intervals to solve the optimization problem of estimating the positions of both the vehicle and diver over time. But with the real ocean forces pushing everything around, this optimization problem blows up quickly.”

On the perception side, Miller’s team has been developing an AI classifier that can process both optical and sonar data mid-mission and solicit human input for any objects classified with uncertainty.

“The idea is for the classifier to pass along some information — say, a bounding box around an image — to the diver and indicate, “I think this is a tire, but I’m not sure. What do you think?” Then, the diver can respond, “Yes, you’ve got it right, or no, look over here in the image to improve your classification,” Miller says.

This feedback loop requires an underwater acoustic modem to support diver-AUV communication. State-of-the-art data rates in underwater acoustic communications would require tens of minutes to send an uncompressed image from the AUV to the diver. So, one aspect the team is investigating is how to compress information into a minimum amount to be useful, working within the constraints of the low bandwidth and high latency of underwater communications and the low size, weight, and power of the commercial off-the-shelf (COTS) hardware they’re using. For their prototype system, the team procured mostly COTS sensors and built a sensor payload that would easily integrate into an AUV routinely employed by the U.S. Navy, with the goal of facilitating technology transition. Beyond sonar and optical sensors, the payload features an acoustic modem for ranging to the diver and several data processing and compute boards.

Miller’s team has tested the sensor-equipped AUV and algorithms around coastal New England — including in the open ocean near Portsmouth, New Hampshire, with the University of New Hampshire’s (UNH) Gulf Surveyor and Gulf Challenger coastal research vessels as diver surrogates, and on the Boston-area Charles River, with an MIT Sailing Pavilion skiff as the surrogate.

“The UNH boats are well-equipped and can access realistic ocean conditions. But pretending to be a diver with a large boat is hard. With the skiff, we can move more slowly and get the relative motion in tune with how a diver and AUV would navigate together.”

Last summer, the team started testing equipment with human divers at Michigan Technological University’s Great Lakes Research Center. Although the divers lacked an interface to feed back information to the AUV, each swam holding the team’s tube-shaped prototype tablet, dubbed a “tube-let.” The tube-let was equipped with a pressure and depth sensor, inertial measurement unit (to track relative motion), and ranging modem — all necessary components for the navigation algorithms to solve the optimization problem.

“A challenge during testing was coordinating the motion of the diver and vehicle, because they don’t yet collaborate,” Miller says. “Once the divers go underwater, there is no communication with the team on the surface. So, you have to plan where to put the diver and vehicle so they don’t collide.”

The team also worked on the perception problem. The water clarity of the Great Lakes at that time of year allowed for underwater imaging with an optical sensor. Caroline Keenan, a Lincoln Scholars Program PhD student jointly working in the laboratory’s Advanced Undersea Systems and Technology Group and Leonard’s research group at MIT, took the opportunity to advance her work on knowledge transfer from optical sensors to sonar sensors. She is exploring whether optical classifiers can train sonar classifiers to recognize objects for which sonar data doesn’t exist. The motivation is to reduce the human operator load associated with labeling sonar data and training sonar classifiers.

With the internally funded research program coming to an end, Miller’s team is now seeking external sponsorship to refine and transition the technology to military or commercial partners.

“The modern world runs on undersea telecommunication and power cables, which are vulnerable to attack by disruptive actors. The undersea domain is becoming increasingly contested as more nations develop and advance the capabilities of autonomous maritime systems. Maintaining global economic security and U.S. strategic advantage in the undersea domain will require leveraging and combining the best of AI and human capabilities,” Miller says.

Muscles are remarkably effective systems for generating controlled force, and engineers developing hardware for robots or prosthetics have long struggled to create analogs that can approach their unique combination of strength, rapid response, scalability, and control. But now, researchers at the MIT Media Lab and Politecnico di Bari in Italy have developed artificial muscle fibers that come closer to matching many of these qualities.

Like the fibers that bundle together to form biological muscles, these fibers can be arranged in different configurations to meet the demands of a given task. Unlike conventional robotic actuation systems, they are compliant enough to interface comfortably with the human body and operate silently without motors, external pumps, or other bulky supporting hardware.

The new electrofluidic fiber muscles — electrically driven actuators built in fiber format — are described in a recent paper published in Science Robotics. The work is led by Media Lab PhD candidate Ozgun Kilic Afsar; Vito Cacucciolo, a professor at the Politecnico di Bari; and four co-authors.

The new system brings together two technologies, Afsar explains. One is a fluidically driven artificial muscle known as a thin McKibben actuator, and the other is a miniaturized solid-state pump based on electrohydrodynamics (EHD), which can generate pressure inside a sealed fluid compartment without moving parts or an external fluid supply.

Until now, most fluid-driven soft actuators have relied on external “heavy, bulky, oftentimes noisy hydraulic infrastructure,” Afsar says, “which makes them difficult to integrate into systems where mobility or compact, lightweight design is important.” This has created a fundamental bottleneck in the practical use of fluidic actuators in real-world applications.

The key to breaking through that bottleneck was the use of integrated pumps based on electrohydrodynamic principles. These millimeter-scale, electrically driven pumps generate pressure and flow by injecting charge into a dielectric fluid, creating ions that drag the fluid along with them. Weighing just a few grams each and not much thicker than a toothpick, they can be fabricated continuously and scaled easily. “We integrated these fiber pumps into a closed fluidic circuit with the thin McKibben actuators,” Afsar says, noting that this was not a simple task given the different dynamics of the two components.

A key design strategy was to pair these fibers in what are known as antagonistic configurations. Cacucciolo explains that this is where “one muscle contracts while another elongates,” as when you bend your arm and your biceps contract while your triceps stretch. In their system, a millimeter-scale fiber pump sits between two similarly scaled McKibben actuators, driving fluid into one actuator to contract it while simultaneously relaxing the other.

“This is very much reminiscent of how biological muscles are configured and organized,” Afsar says. “We didn’t choose this configuration simply for the sake of biomimicry, but because we needed a way to store the fluid within the muscle design.” The need for an external reservoir open to the atmosphere has been one of the main factors limiting the practical use of EHD pumps in robotic systems outside the lab. By pairing two McKibben fibers in line, with a fiber pump between them to form a closed circuit, the team eliminated that need entirely.

Another key finding was that the muscle fibers needed to be pre-pressurized, rather than simply filled. “There is a minimum internal system pressure that the system can tolerate,” Afsar says, “below which the pump can degrade or temporarily stop working.” This happens because of cavitation, in which vapor bubbles form when the pressure at the pump inlet drops below the vapor pressure of the liquid, eventually leading to dielectric breakdown.

To prevent cavitation, they applied a “bias” pressure from the outset so that the pressure at the fiber pump inlet never falls below the liquid’s vapor pressure. The magnitude of this bias pressure can be adjusted depending on the application. “To achieve the maximum contraction the muscle can generate, we found there is a specific bias pressure range that is optimal,” she says. “If you want to configure the system for faster response, you might increase that bias pressure, though with some reduction in maximum contraction.”

Cacucciolo adds that most of today’s robotic limbs and hands are built around electric servo motors, whose configuration differs fundamentally from that of natural muscles. Servo motors generate rotational motion on a shaft that must be converted into linear movement, whereas muscle fibers naturally contract and extend linearly, as do these electrofluidic fibers. 

“Most robotic arms and humanoid robots are designed around the servo motors that drive them,” he says. “That creates integration constraints, because servo motors are hard to package densely and tend to concentrate mass near the joints they drive. By contrast, artificial muscles in fiber form can be packed tightly inside a robot or exoskeleton and distributed throughout the structure, rather than concentrated near a joint.”

These electrofluidic muscles may be especially useful for wearable applications, such as exoskeletons that help a person lift heavier loads or assistive devices that restore or augment dexterity. But the underlying principles could also apply more broadly. “Our findings extend to fluid-driven robotic systems in general,” Cacucciolo says. “Wherever fluidic actuators are used, or where engineers want to replace external pumps with internal ones, these design principles could apply across a wide range of fluid-driven robotic systems.”

This work “presents a major advancement in fiber-format soft actuation,” which “addresses several long-standing hurdles in the field, particularly regarding portability and power density,” says Herbert Shea, a professor in the Soft Transducers Laboratory at Ecole Polytechnique Federale de Lausanne in Switzerland, who was not associated with this research. “The lack of moving parts in the pump makes these muscles silent, a major advantage for prosthetic devices and assistive clothing,” he says.

Shea adds that “this high-quality and rigorous work bridges the gap between fundamental fluid dynamics and practical robotic applications. The authors provide a complete system-level solution — characterizing the individual components, developing a predictive physical model, and validating it through a range of demonstrators.”

In addition to Afsar and Cacucciolo, the team also included Gabriele Pupillo and Gennaro Vitucci at Politecnico di Bari and Wedyan Babatain and Professor Hiroshi Ishii at the MIT Media Lab. The work was supported by the European Research Council and the Media Lab’s multi-sponsored consortium.

Did you know your Samsung TV can double as a SmartThings Hub? Many 2024 and newer models come with the hub built in, which means no extra device is needed. With just a few steps, you can turn your TV into the heart of your smart home and instantly start connecting devices. Read on for a step-by-step guide to activate your SmartThings Hub. 

How it Works

There are two easy ways to activate the SmartThings Hub built into your TV: directly from your mobile phone using the SmartThings app, or through the SmartThings app on your TV.

Both options follow a similar flow, connect your TV, enable the hub, and start adding devices, so you can choose whichever is most convenient for you.

Activate the Hub Using Your Galaxy 

If you already use SmartThings on your phone, this is often the fastest way to get started.

Step 1: Turn On Your TV

• Make sure your Samsung TV is powered on and connected to Wi-Fi.

Step 2: Open SmartThings on Your Phone

• Launch the SmartThings app on your mobile device. 
• Confirm you’re signed in with the same Samsung account used on your TV.

Step 3: Find Your TV

• Tap Devices in the app. 
• Select your TV from the list.

Step 4: Open Hub Settings

• Tap the Featured icon at the bottom
• SmartThings Hub shows up on the next screen 

Step 5: Activate the Hub

• Follow the on-screen prompts to turn the hub On.
• Wait while SmartThings connects to your TV and completes setup.
• Once finished, your TV is officially activated as a SmartThings Hub.

Activate the Hub Using Your TV

You can also turn on the hub directly from your TV using the built-in SmartThings app.

Step 1: Turn on Your TV

• Make sure your Samsung TV is powered on and connected to Wi-Fi.

Step 2: Open the SmartThings App on Your TV

• Press the Home button on your remote.
• Scroll over to Connected Devices
• Navigate to and open the SmartThings app.

Step 3: Access Settings

• Select the Settings icon (cog wheel) in the SmartThings app. This may also be featured already on the home page.
• Scroll down and choose SmartThings Hub.

Step 4: Activate the Hub

• Toggle SmartThings Hub to On.
• The Hub is now active!

Step 5: Add Devices

Once your Hub is activated:

• In the SmartThings app, tap + Add device.
• Scan for Matter or other supported devices.
• Import them into SmartThings.

That’s It!

Your Samsung TV is now a fully functioning SmartThings Hub. From here, you can control smart lights, plugs, sensors, and more, all without additional hardware. 

With the Hub activated, your TV becomes more than just a screen; it’s now the command center for your connected home. Whether you’re dimming lights for movie night, automating your thermostat when you leave home, or linking new Matter devices as they hit the market, SmartThings makes it seamless. 

Need devices to start building out your smart home? Shop them now at https://www.samsung.com/us/smartthings/all-smartthings/