Tag Archives: smart homes

Edge Computing for Smart Homes

Designing devices for smart homes can be a huge challenge. There are numerous limitations to be overcome, but the sensible use of sensors can help smooth the way. Devices for smart homes can relate to lighting, kitchen appliances, security, heating/cooling, and entertainment. With the advancement in technology for smart homes, engineers need to be more intuitive and develop more capabilities for making products more intelligent. Among the expectations from homeowners are faster response, higher performance, higher levels of accuracy, and easier integration of multiple devices.

Today, there are widely varying intelligent devices in modern intelligent home technology. Most often, these produce massive amounts of data that must be processed quickly. Although there are limitations to improving the technology for smart homes, contextual data can address them by using a combination of sensors, with the device processing them on the field rather than doing it in a cloud.

Just like in any technology, the fundamental systems and components of smart home technology are also constantly improving. Engineers must continuously develop better solutions as soon as they recognize the limitations. Among the several limitations, three major ones that plague smart home technology are accuracy, latency, and compatibility.

Accuracy is an extremely important factor in smart home technology. Everything affects accuracy, starting from the sensors that are necessary to collect data to the artificial intelligence tools that process the data. This is leading engineers to collect data using innovative new approaches, including using algorithms to combine multiple sensors for processing the data so that they can achieve a higher level of accuracy.

For instance, a smart home security system may involve radar, computer vision, and sound detection to accurately predict the presence of a person. Engineers are also using AI tools and algorithms for finding the most efficient methods of processing data. However, this leads us to the next limitation—latency.

Latency negatively impacts any type of smart home technology. Home security, for instance, needs collecting data from multiple sensors, and analyzing them as fast as possible. The impact on latency increases as there is an increase in the data gathered, transmitted, and processed.

With end users having multiple smart systems working concurrently, compatibility challenges are bound to crop up, impacting overall performance and functionality. This is one reason for engineers to move their focus from systems that depend on platforms, manufacturers, and devices. Rather, they are moving more of the functionality and processing to the devices themselves. This is where edge computing is helping them—addressing all three challenges at a time.

In smart home technology, edge computing transfers most of the processing and analysis from the cloud to the device itself. In simpler terms, data processing takes place as close to the sensor as possible.

For instance, home security cameras are notorious for reporting false positives, eventually causing the owners to ignore accurate alerts. One way of improving the accuracy is by improving the quality of the lens and image sensors. The other is by using edge computing to differentiate between the movement of animals and leaves being moved by winds.

Radar Sensors for Smart Homes Enable Energy Efficiency

With the increase in the application of smart homes, the number of connected devices is also growing. Although this is making the lives of users more convenient, it is also resulting in an increase in energy consumption. This is due to the devices being either permanently active or in standby mode, ready for use at all times, even when there is no one home. Now Infineon is offering their radar sensor, the XENSIV, to make smart homes become more energy-efficient.

By an estimate, at present, there are more than 200 million smart homes around the world. This number is forecast to exceed 500 million by the end of a few years in the future.

The use of digital devices with increasingly ingenious functionalities helps to make houses smarter. However, there is a flip side to this—the increase in energy consumption—despite most modern devices showing a trend of steadily decreasing standby power consumption. This is because most smart devices need power even when they are in standby mode, to be capable of reacting instantaneously to user input. On many occasions, it is not at all necessary for a device to run in standby mode, consuming energy, primarily when there is no one present.

The radar sensor from Infineon aims to solve this issue while meeting the requirements of both digitization and energy efficiency. Capable of operating in almost all smart home systems, radar sensors are highly sensitive devices. They can detect the presence of a person and whether a device needs to be ready. This action is similar to that of the screensaver that kicks-in in on the monitor of a personal computer, when there is no activity from the mouse or keyboard after a certain time but reactivates the monitor as soon as the mouse or keyboard detects a new input. The truly smart and energy-saving device from Infineon, operating at 60 GHz, performs a reliable detection of the absence or presence of a human.

Devices like smart speakers, thermostats, and digital assistants consume very little power when in their normal standby mode. However, their energy consumption can reduce still further if they are forced into a deep sleep mode, especially when no one is around. Doing this can save a few more watts of power.

Other devices like a TV, laptop, sound system, or the air-conditioner can consume several 100 Watts when they are on. Switching them off when no one is likely to use them soon, such as when no one is present at home, can therefore save a lot of energy.

The radar-based smart device continuously checks to sense if there is anyone present or is moving about. If it detects there is no one present, it can switch other devices to a deep-sleep mode or switch them off entirely, thereby helping to save energy. The radar module consumes only about 0.1 W, and this is significantly lower than the energy demands of many other devices, even when they are in their standby mode.

What is Ambient Sensing?

Although smart homes have been around for several years now, this industry is rather nascent. Even though we are familiar with the use of Amazon Alexas and Google Homes as smart devices, but for smart homes, they have their limitations.

Smart devices do use technologies promising levels of interoperability and convenience that were unheard of a few years ago. However, they have not been able to fulfill current expectations. For instance, they struggle if there is no home network, cannot use unprocessed data, and are typically standalone devices.

Movies provide a better concept of a smart home. They present a futuristic building with levels of autonomy and comfort far beyond what the current technology can provide. In the real world, our ability to interact with them is rather limited.

For instance, the smart technology available at present allows interaction with voice commands only, thereby limiting their autonomy. Although the current technology boasts of voice recognition, this is still frustrating and cumbersome to use. Most people seek a seamless experience that comes with higher intuitive or human interaction.

For instance, it is still not possible to unlock a smart home simply by improving voice commands. Although audio sensors do form a crucial element for intuitive interaction with a smart home, making them a part of a sensor array for providing better contextual information would be a better idea. For genuinely smart home, the devices must provide a more meaningful interaction, including superior personalization for contextualized decision-making.

While it may be possible for manufacturers to pack in unique sensor arrays in devices, some sensor types could prove to be more useful. For instance, cameras provide huge amounts of information, and smart systems could make use of this fact to perceive the smart home in a better way. Adding acoustic sensors, and gas sensors along with 3-D mapping could be one way of bringing smart environments to the next level.

By collating these inputs, smart devices can understand and implement individual preferences better. For instance, depending on who has entered or exited the room, a smart device can change the sounds, lights, safety features, and temperature matching that person’s profile. Smart devices must not limit themselves to comprehending the ambient alone, but be capable of changing the environment, even without direct inputs.

These features could go beyond providing comfort alone. For instance, with motion sensors, the device could extend security. Along with motion sensing, individual recognition, and 3-D mapping could make homes much safer. For saving energy, sensors for presence, daylight sensing, and temperature measurements could dim lights or adjust air conditioning for better comfort on hot days.

One of the issues holding back such implementation is consumer privacy. While homeowners have grown accustomed to smart speakers, endless examples are available of data-mining organizations that observe the consumer’s daily interaction with these devices. For instance, Amazon’s Astro robot has been accused of data harvesting and there is criticism of Facebook’s smart glasses by the Data Privacy Commission in Ireland. As devices get smarter and use more ambient technology, consumers will have to share greater amounts of data than they are doing at present.