The development of wearable electronic systems, whether biometric, communication or virtual reality, extends the concept of embedded systems to new and unknown areas. Putting sensors and output devices on the operator creates a new word - the electronic man: a combination of human and embedded systems.
Wearable systems open up new horizons for real-world applications and need to revisit the embedded architecture. The sensor group used in a stickable or ingestible manner is completely isolated from traditional power, ground and I/O connections. To achieve small size and near-zero power consumption, small sensor groups support traditional local signal processing, storage, and wireless interconnection, and are not limited to this. This is a dilemma that designers must solve.
Separate the systemOne way to solve the problem of wearable systems is to refer to traditional embedded system designs, which include sensors, actuators, and displays that connect to the user's body. Driven by mobility, comfort and hidden demand, systems need to be separated. After the sensors, output devices, and computing resources are physically separated from each other, take a look at what happens to the system architecture.
As an example, refer to the design of smart glasses. To avoid clichés, we don't discuss consumer products that we are familiar with, but look at the glasses designed by industrial equipment supplier XOEye. These glasses are used for component observation, inventory processing, and on-site maintenance. The system features a stereo-mounted 720-line video camera, voice input, and LED and voice output, designed to help people perform some pre-defined tasks in an interactive manner.
Xonye Chief Technology Officer Jon Sharp explained that the glasses capture and analyze the stereoscopic images seen by the user, enhancing the resolving power of the components, and measuring the size and shape without physical contact or measuring tools during the repair process. Interact with the technician - "Adjust the screws on the left side first" or warn of possible safety hazards with a flashing red LED. "Don't go there!"
This traditional method of design uses a camera and microphone mounted on the glasses, then performs video processing, target recognition, and establishes a wireless communication link through the backpack and battery behind it. For this design, the traditional user response is to look at the backpack and then carefully bend down to use the system.
Let us enter the concept of wearable technology. XOEye's approach is to achieve completely autonomous glasses. This goal clearly has space and power constraints. We can't magic, and these restrictions force some calculations to be done remotely, usually in the cloud. But dividing the computational load also brings new design challenges.
Establish linkOn the Internet of Things (IoT), moving a large number of computing tasks to the cloud is not a new concept. Chakra Parvathaneni, senior director of business development at Creative Technology, points out that this division varies from application to application. He noticed that "the home thermostat has a lot of local processing tasks, but Apple's Siri is almost in the cloud."
In the case of XOEye, moving tasks to the cloud means either having enough bandwidth to deliver two streams of video in the original format or performing video compression in real time in the glasses. The latter is feasible with existing media processing chips, but with a properly sized battery. However, there is another problem.
Sharp reminds, “Even if there is no link, you must maintain the human interface and some features. For example, when you lose your WiFi connection, be sure to identify security issues in real time.†Some features require a certain degree of continuous real-time response. — Cloud computing at the far end of the Internet is not guaranteed.
These problems require local processing that contradicts the size, weight, and power consumption limitations of the glasses. XOEye originally wanted to solve this problem by using the OMAP architecture combined with the MCU and the accelerator. The OMAP SoC can handle traditional media processing tasks, but Sharp laments that "real-time stereo ranging is not possible." So, XOEye turned to CPU plus FPGAs, and they were able to build energy-efficient applications no matter what tasks they needed. Local accelerator.
Smart hubEven if the operating conditions are guaranteed to be locally interconnected with the wireless hub, the unresolved uncertainty from the hub to the cloud via the Internet will introduce unacceptable uncertainties. This is one of the structural challenges facing IoT. With these in mind, if you want to do some computing tasks outside of your wearable device, you can put it on your local wireless hub instead of the cloud. Of course, this can't just use a commercial WiFi hub.
Integrating compute nodes in a WiFi hub dramatically increases the flexibility of system design. In contrast, hubs are generally unrestricted in terms of space and power consumption, so you can put some computing and storage resources there. Short-range WiFi links provide reliable broadband, predictable latency connections, and support for hubs to participate in critical control or human-machine interface loops, where unexpected delays can cause problems. Moreover, the hub has a multitasking CPU and corresponding accelerators that perform the processing tasks of many remote wearable devices.
Smart radioWhat if the wearable device is much smaller than the glasses, such as a wristband, a device that is placed in the shoe, and a larger pill? If there is not enough space to accommodate a large battery, it will not be able to support high power, and WiFi will not remain connected. The wireless mode turns to Bluetooth or short-distance links with very low power consumption. The hub is now itself a wearable device, mounted on a belt or pocket, within a meter of the sensor — if it only supports near-field wireless links, it can be very close. The task partitioning problem has changed in a very interesting way.
Some of the difficulties have contributed to the development of wearable devices. At a minimum, include sensors, controllers that query these sensors, and wireless interfaces. Careful adjustment of the duty cycle, tiny batteries can support these loads - low energy devices. But where is the calculation now?
The bandwidth between the sensor and the first stage sensor processing becomes a significant problem. Can a wireless link carry raw data streams from sensors in real time? If not, can some energy consumption be spent on improving link bandwidth or local processing of sensors? If the system user model changes, will the answer be different?
One way to solve this problem is to rethink the RF. Designers tend to place the baseband processor in the wireless interface as an anti-jamming black box. However, Parvathaneni of the Creative Technology Company recommends an in-depth understanding of its internals. For example, Creative Technologies has a range of radio frequency processing unit (RPU) baseband processor subsystems that give system designers more freedom in two ways.
Parvathaneni said that internally, the Ensigma RPU) includes a generic MIPS CPU core supported by a special set of accelerators. Therefore, the functionality is software defined and the user can modify the code to change the RF air interface. This is the freedom on the one hand, you can adjust the power consumed by the baseband to match the bandwidth and distance requirements of a particular wireless link. Parvathaneni also explained: "In many cases, the air interface leaves room for the MIPS core for the main task." Therefore, the system designer can choose the air interface standard and then load a set of processing tasks into the RPU. Changing the hardware design can be done at any time to cope with changes in the operating mode of the wearable system. In some cases, this flexibility avoids the use of an MCU or compression engine at the sensor location.
Development of wearable electronic systems - the combination of human and embedded systems (electronic engineering album)
Wearable sensors are getting smaller, lighter, and almost disposable, so issues such as hardware and power consumption to support the air interface are becoming more important. In this regard, IP startup Epic Semiconductor made a very interesting suggestion that the wireless link does not use RF, but other. According to Epic's CTO, Wolf Richter, the approach is to use an electric field.
Epic has developed a technology that uses external electrodes for three different purposes - small conductor sheets or conductor foils. First, the circuit draws energy from the surrounding electric field. Within three to five seconds, the device is able to collect enough energy to power the 5 mW load for a period of time. Richter cited an example of performing a task on an ARM Cortex-M0 running at 3 MHz, rewriting a 15V electronic ink non-volatile display, or briefly activating a 30V printed circuit.
Second, Epic Intellectual Property (IP) is able to detect any physical phenomenon of the modulated electric field, just like a typical capacitive sensor. Richter said, for example, the device can detect people appearing around three meters. Other more common applications include measuring the dielectric constant of a nearby object surface from which the system can infer the temperature, pulse, and muscle activity of the birthed object. Alternatively, in a completely different environment, the sensor can infer the degree of spoilage of the packaged meat surface from changes in the media constant.
Finally, this technique can use the same electrode on a bidirectional signal to achieve RF-free near field communication by monitoring and modulating the electric field on the electrode. In this way, a 0.25 mm2 silicon can provide power, sensing, and interconnect for smart surfaces, patches, or some similar media.
Some things that are dividedWe can think of wearable systems as traditional embedded systems, and extreme mobility imposes unusual size, weight and power constraints on each component. The effect of these restrictions is to divide the system apart from the main body, with only the wireless link connecting the two parts. In the case of smart glasses, the system remains the same, with only a large amount of storage and the most cumbersome computing tasks being put into the cloud via IoT.
In complex biometric systems, separate patches, straps, and placement sensors leave the central unit, each with a short-range wireless link, enough computing power to manage bandwidth, and perform local control loops. The system will be completely distributed, and the central unit will only be used as a hub for short-range wireless connections, allowing cloud resources to be connected via WiFi or cellular networks.
Implementing such a system sounds very simple. Find out the physical topology and where the sensor is. Select the wireless link that the distance and data rate can be supported by the sensor and topology. Select local computing and power supply design to meet the sensor's local control loop requirements, providing the data compression, error correction, filtering, and broadband processing requirements required for wireless links. Repeat until it is complete.
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