Design compact, high-performance patient monitoring devices using dense, flexible interconnects

With the increased need for monitoring of many chronic diseases and physical conditions, the use of patient monitoring devices is rapidly expanding as they are critical to speeding healing, avoiding complications and maintaining optimal health. A typical patient monitoring device interconnection system transfers data (sometimes including high-resolution images), power, and control signals within and between devices. Designers of these systems must contend with numerous and often conflicting challenges, including smaller form factors, greater feature sets, and faster data rates that require high signal integrity (SI) and smooth data transfer.

Author: Jeff Shepard

With the increased need for monitoring of many chronic diseases and physical conditions, the use of patient monitoring devices is rapidly expanding as they are critical to speeding healing, avoiding complications and maintaining optimal health. A typical patient monitoring device interconnection system transfers data (sometimes including high-resolution images), power, and control signals within and between devices. Designers of these systems must contend with numerous and often conflicting challenges, including smaller form factors, greater feature sets, and faster data rates that require high signal integrity (SI) and smooth data transfer.

At the same time, these devices must be comfortable for the patient and, despite the monitor’s inherent complexity and criticality of its functionality, be easy to use (when appropriate) for both the caregiver and the patient. Using bulky, inappropriate, or poorly designed connectors or interconnects can defeat these goals and add unnecessary costs.

To meet the requirements of these applications, the market provides designers with a number of increasingly sophisticated connector and interconnect device options. For example, depending on the needs of a specific application, designers can choose flat-flex (FPC) high-density connectors for low-cost automated assembly, or flexible printed cables with fine center-to-center spacing where wire-to-board solutions are impractical ( FPC), or choose a USB Type-C® connector that provides a compact, easy-to-use, high-speed connection.

This article briefly reviews the interconnection requirements of patient monitoring devices, exploring the connections within the device and between the device and the outside world. Molex’s FFC, FPC, and USB Type-C connectors are then presented with examples, discussing their key features and benefits, and how to apply them correctly.

Board-to-Board Interconnect Requirements

The combination of FFC and FPC can support designers’ needs for high-density and high-speed board-to-board interconnection systems for patient monitoring equipment. Some of these connectors are available for manual and robotic assembly operations and feature single-step mating with an automatic locking mechanism (Figure 1).

Design compact, high-performance patient monitoring devices using dense, flexible interconnects
Figure 1: FFC and FPC connectors are available for manual and robotic assembly operations and feature single-step mating capabilities with an automatic locking mechanism. (Image credit: Digi-Key Electronics)

FFC board-to-board connectors can be used to support data rates up to 40 gigahertz (GHz) and provide up to 80 connections in multiple low-profile orientations, including right-angle and vertical orientations, enabling design flexibility choose. The connection pitch can be less than one millimeter (mm) to support narrow package designs. Zero Insertion Force (ZIF) and non-ZIF designs are available to meet specific application needs.

Some FFCs are specified for temperatures up to 150 degrees Celsius (°C) and can be used in a variety of cabling options, including general-purpose FFC cables, locking FFC cables, or custom FFC cables. These connectors typically accept standard or shielded FFCs, and ground terminations support the needs of high-speed protocols such as low-voltage differential signaling (LVDS). For maximum performance, shielded cables should be used with connectors that have ground terminals.

Connect patient monitors to the outside world

Patient monitoring is critical for caregivers because it helps them understand how the body responds to therapies that lessen or repair the effects of disease or other bodily ailments. This often requires sending the monitored data to a device other than the monitoring device.

The USB Type-C connector can be the best choice for connecting patient monitoring equipment to external devices such as HDMI displays and data storage systems. These connectors feature a symmetrical and reversible pin layout for ease of use and flexibility as they can be connected in any orientation (Figure 2).

Figure 2: The USB Type-C connector has a symmetrical and reversible pinout for ease of use and flexibility. (Image credit: Digi-Key Electronics)

Implementation of the latest USB4 protocol must use a USB Type-C connector. Based on the Thunderbolt 3 interface, USB4 allows DisplayPort and PCI Express (PCIe) data to be tunneled and supports a nominal data rate of 20 gigabits per second (Gbits/s) and is scalable to 40 Gbits/s. With the ability for multiple end device types to dynamically share a single high-speed link, USB4 can optimize data transfer by type and application. Therefore, the nominal 20 Gbit/s data rate when sending mixed data can result in higher effective throughput than USB 3.2 when tunneling is used.

The USB Power Delivery (PD) protocol provides up to 20 volts, 5 amps (A) and 100 watts for charging and other uses, including expanding data transfer capabilities. Compared to the 1.8 A charging capability of Micro USB 2.0, USB Type-C PD can reduce battery charging time by 40% to 64%. The intelligent and flexible system-level power management of USB PD supports bidirectional power supply, which can switch directions in real-time, making it possible for Type-C to support other standards such as DisplayPort, HDMI or PCIe.

Fast Role Swap (FRS) is an improvement in the latest version of the USB Type-C PD specification. Designers can use FRS to reduce the risk of data loss and maintain the signal integrity of USB peripherals such as patient monitoring equipment if the power cord is accidentally removed from the hub or cradle. FRS is implemented in 150 microseconds (μs), allowing the battery to be the source and the other devices to be the drain and keep running uninterrupted. Data communication continues uninterrupted in a single direction, keeping the system running and preventing failures even if the power direction is reversed.

Another enhancement to USB PD performance under USB4 is Programmable Power Supply (PPS) capability. PPS enables small step regulation of voltage and current. If a power outlet is connected to a PPS-capable power source, it can request that the power delivered by the power source be changed. PPS enables fast charging of lithium-ion batteries, improving the power efficiency of the overall system, reducing thermal loads, and enabling higher system packing densities.

Board-to-Board Connectors for Medical Monitoring Equipment

As mentioned above, the combination of FFC and FPC addresses the needs of patient monitoring device designers for high-density and high-speed board-to-board interconnect systems, while supporting manual or robotic assembly. Model 0541324062 in Molex’s Easy-On FFC/FPC connector family is a good example. The connector has 40 positions, gold-plated contacts, and 0.50 millimeter (mm) pitch (Figure 3).

Figure 3: The Molex Model 0541324062 Easy-On FFC/FPC connector has 40 positions, gold plated contacts, and 0.50 millimeter (mm) pitch. (Image credit: Molex)

The 0541324062 model supports data rates up to 10 Gbits/s. Full cable insertion and secure mating with active inertia lock. A cable retention force of 20 Newtons (N) ensures shock and vibration resistance. Robust solder lugs bring retention and strain relief to the printed circuit board.

Molex’s Premo-Flex Model 0151660431 FFC patch cords have a 0.50 mm pitch and a 102.00 mm length (Figure 4), when used with the Model 541324062 Easy-On FFC/FPC Connector, to align with the connector’s 40 pin positions patch. This board-to-board interconnect system can help designers address challenges in applications where space is constrained or difficult to reach.

Figure 4: Molex’s 0151660431 0.50 mm pitch Premo-Flex FFC jumper has 40 positions and is 102.00 mm long. (Image credit: Molex)

Molex offers Premo-Flex patch cords in a variety of cable lengths, circuit sizes, pitches and thicknesses. These durable, ultra-flexible cables are rated to 105°C and have a flex life of 900,000 cycles compared to 6,000 cycles for standard patch cords.

Note that when connecting or disconnecting the FFC jumper from the Easy-On FFC/FPC connector, you must ensure that all connections are de-energized to avoid sparks that could damage the contacts. In addition, when opening or closing the lock, you should apply force on both sides of the lock at the same time. Applying force to only one side may damage the connector. Finally, when inserting the flex cable into the connector, there shouldn’t be any pull or tension on the cable. Otherwise, the locker may not lock properly, the cable may be damaged, or the line may be cut.

High-speed external connections

Molex USB Type-C series connectors such as the 1054500101 can support trouble-free patient monitoring data transfer and high signal integrity while providing power to the device (Figure 5). Molex uses three insert molding processes in its USB Type-C connectors, making the mating tongues a single piece and minimizing water ingress. With three additional insert molding processes, the risk of terminal pull-out or bending is minimized, resulting in higher mechanical durability and electrical reliability. These connectors provide a durable solution, rated to 10,000 mating cycles, to withstand improper insertion attempts and other abuse.

Figure 5: A USB Type-C connector like the 1054500101 can support trouble-free data transfer and provide power to medical monitoring equipment. (Image credit: Molex)

These high-performance connectors have the following characteristics:

・ Up to 40 Gbit/s data rate to support high-speed network applications
・ Supports 4K resolution high-quality monitors
・Shield providing EMI/RFI protection
・ Prevent electrical shorts during mating by using tape plugs between the housing and the housing.
・ Stable electrical performance, supporting higher current capacity and minimal temperature rise

The increased power capacity of the USB Type-C connector enables smaller pin spacing, which means designers need to be aware of potential safety and fire hazards in the event of thermal runaway. Under normal circumstances, the USB PD power rules ensure safe operation. However, damage to the connector or cable can result in unsafe operation. Overcurrent and overtemperature protection devices are often included in the design of USB Type-C connectors and cables to reduce the possibility of thermal runaway.

The SuperSpeed ​​transmission differential pair in a USB Type-C cable has a differential impedance of 90 ohms (Ω). Designs using alternate mode must also be able to handle 90 Ω.


As the need for patient monitoring increases, designers of such systems require connectors and associated interconnecting cables and patch cords that can reliably transmit multiple types of high-speed data as well as power and control signals to and from the patient send out. These connections must often be made in tight spaces with minimal cost, while ensuring ease of use and minimal impact on patient comfort.

As mentioned above, the advent of FFC, FPC, and USB Type-C connectors addresses these challenges with efficient assembly capabilities, high signal integrity, and greater ease of use. With the right combination of these connectors and interconnects, designers can address the inherent complexities of patient monitoring, from electrical performance to quality of care.

The Links:   ME701203 DMF-51043NFU-FW-1

Attention | 15 illegal apps are suspected of collecting personal privacy information beyond the scope

The National Computer Virus Emergency Response Center recently discovered through Internet monitoring that 15 mobile applications have privacy violations, violated the relevant provisions of the “Network Security Law”, and were suspected of collecting personal privacy information beyond the scope.

1. Failure to expressly apply for all privacy rights to the user is suspected of non-compliance with privacy. The 13 apps involved are as follows:

“Nut Cloud” (Version 4.23.3, 360 Mobile Assistant), “Fish Ear Voice” (Version 5.23.5, 360 Mobile Assistant), “Parking Expert” (Version 5.1.9, OPPO Software Store), “Show” (Version 4.9.1, vivo app store), “Luban Music Label” (version 6.9.4, vivo app store), “Mala Mara” (version 4.7.16, vivo app store), “The Most Beautiful Weather” (version 7.1.1, vivo app store), “Football Fortune” (version 4.3.2, Huawei App Store), “91 Sports” (version 3.8.5, Huawei App Store), “Palm Input Method” (version 3.5.0, Huawei App Store), “Star Life” (Version 2.0.004, Meizu App Store), “Trend Players” (Version 3.3.6, App Store), “Zhongtuo Gang” (Version 3.9.3, App Store).

2. The personal information provided by the app to the third party is not anonymized, which is suspected of non-compliance with privacy. The 1 App involved is as follows:

One Jar (version 3.14.9, App Store).

3. Failure to provide effective functions for correcting, deleting personal information and canceling user accounts, or setting unreasonable conditions for canceling user accounts, is suspected of privacy violations. The 4 apps involved are as follows:

“Fish Ear Voice” (version 5.23.5, 360 Mobile Assistant), “Palm Input Method” (version 3.5.0, Huawei App Store), “Star Life” (version 2.0.004, Meizu App Store), “Big Head” Doll” (version 2.7.0, App Treasure).

4. Failure to establish and publish personal information security complaint and reporting channels, or exceed the promised response time limit, which is suspected of privacy violations. The 1 App involved is as follows:

“Starway Life” (version 2.0.004, Meizu App Store).

In response to the above situation, the National Computer Virus Emergency Response Center reminds the majority of mobile phone users to download and use the above illegal and illegal mobile apps with caution, and at the same time, pay attention to carefully read the user agreement and privacy policy description of the app, and do not open and agree to unnecessary privacy rights. Do not enter personal privacy information at will, maintain and clean relevant data on a regular basis, and avoid leakage of personal privacy information.

The Links:   LQ080V3DG01 PMH150CS1D060

Smart doorbell design two or three things: video, audio and power technology

For security purposes, video doorbell technology is widely used in residential, commercial and industrial facilities to replace traditional high-priced CCTV networks without the need for transmission media such as coaxial cable or Ethernet. This article examines some designs related to video doorbells Problems, and around the video, audio and power technology, to give relevant embedded developers a reference.

For security purposes, video doorbell technology is widely used in residential, commercial and industrial facilities to replace traditional high-priced CCTV networks without the need for transmission media such as coaxial cable or Ethernet. This article examines some designs related to video doorbells Problems, and around the video, audio and power technology, to give relevant embedded developers a reference.

seamless user experience

Traditional video doorbell systems involve keys, microphones, and cameras. These systems are usually hardwired to power and the video is routed to specific monitors. Video doorbells for IoT have a similar architecture but are implemented very differently. Motion sensors detect visitors walking to the door and stream video via the cloud to a smartphone or cloud storage. Communication with visitors takes place via bidirectional IP audio streaming and bidirectional video streaming running in the application. The basic functionality of these doorbells can be integrated with a complete security system that can remotely enable/disable keyless locks, trigger alarms or provide automatic feedback based on specific inputs.

Early versions of video doorbells were often plagued by video and audio issues, such as false ringtones and choppy audio, but key features like cloud backup, motion detection, video streaming, and two-way communication required seamless connectivity to be commercially viable. value. These requirements, combined with previous hard-wired power limitations, present modern video doorbell subsystems with their own set of hardware challenges.

error action event

Thermoelectric (aka passive infrared) sensors commonly used in video doorbells are prone to errors, such as incorrectly responding to glare from vehicles driving during the day, gusts of warm wind, bugs, animals, and a wide variety of other objects. Heat-based activity and in the process trigger annoying false alarm tones and notifications on the user’s phone. This greatly reduces the security of a video doorbell as users will eventually ignore the alarm entirely, or even take the doorbell offline. In addition, the frequent occurrence of false motion detection events by PIR sensors can greatly reduce battery life.

A relatively simple solution is to use two PIR sensors with slightly overlapping coverage to create a larger motion detection area (Figure 1). Since the dual sensors only generate notifications for larger objects, smaller objects such as bed bugs and pets will go undetected. Use PIR sensors with other light sensors and temperature/humidity sensors to avoid false triggering due to rapid changes in temperature or light. This multi-modal sensing approach reduces the possibility of false alarms, while also reducing overall power consumption, thereby extending battery life.

Figure 1 Redundant PIR sensors improve the accuracy of human motion detection,
Because multiple beams must be fired for it to be considered a motion event.

Algorithm-based motion detection can also be implemented using an embedded MCU and some firmware to improve accuracy. There are various ways to achieve visual motion based detection, but one of the most common is to compare the current frame to a reference image and track the differences pixel by pixel. This type of image processing must be smart enough to process motion from windmills and trees as part of the background to avoid false positives, a capability that requires considerable processing power.

Some of these filtering tasks can be transferred to cloud-based algorithms that fine-tune image data for specific customers. But this would require relatively large infrastructure to provide support and a good Wi-Fi connection, and would still be high power consumption. So a battery-powered smart doorbell isn’t a smart choice — at least for now. While being able to rely on external power reduces the doorbell’s location options, it also doesn’t require charging or battery replacement.

Image sensor and processor interface issues

Image processing in a video doorbell requires an image sensor, a digital multimedia processor, and in most cases, some peripherals. When choosing an image sensor, there are several things to consider, the most important of which are resolution, frame rate, pixel size, pixel structure, and shutter time. In addition to the many considerations of individual components, there are often interface issues between image sensors and digital media processors.

Unless you pay special attention, you may find that your devices cannot communicate with each other because of mismatched input/output (I/O) interface formats. Because of the large number of differences in the I/O interfaces (I2C, parallel, general purpose I/O), errors like this are much more common than one might think. To avoid this unpleasant situation, designers must ensure that the I/O interface supported by the image sensor is compatible with the I/O of the digital media processor.

Similar problems can arise when two devices have different operating voltages and logic signal levels. Fortunately, voltage converters can easily resolve this mismatch with bidirectional voltage conversion in the range of 0.6 to 5.5 V, and although they add little cost to the product’s BOM, voltage conversion devices provide designers with A wider range of sensors to compensate for this investment, in the past the sensor and MCU had to use the same matching voltage.

environment prone to noise

The full-duplex communication required for modern video doorbells adds additional complexity, requiring the design to deal with erratic feedback caused by the user adjusting the speaker/microphone gain too high. For example, the person receiving the audio needs a relatively large gain on the speaker to adequately discern what the far end is saying, but the close range of the microphone easily detects the sound and often amplifies it, causing bad echoes (Figure 2). In the past, half-duplex communication mitigated this echo by significantly reducing the microphone’s gain when the signal was received by the speaker.

Figure 2 Two-way audio communication requires careful consideration in terms of reverberating speech and echoes

Systems that actively adjust microphone and speaker gain may correct this for full-duplex communication in environments with relatively low ambient noise levels. Unfortunately, this doesn’t work well in environments with unpredictable sources of ambient noise, such as passing buses or other traffic. There are several digital signal processing (DSP) techniques that can address this problem, including Acoustic Echo Cancellation (AEC) and Adaptive Spectral Noise Reduction (ASNR). AEC creates adaptive filters that effectively cancel echoes by initially identifying the transmitted signal and canceling it when it reappears within a certain time window. ASNR utilizes the frequency domain to remove ambient noise and unwanted noise components from the audio signal, thereby removing background noise and broadband noise. AGC is designed to improve the low frequency speech signal of hands-free communication. Audio algorithms such as these provide a superior audio experience by maintaining microphone and speaker gain without unwanted feedback and echoes or resorting to voice switching.

Get the most out of your speakers

While complex DSP algorithms help enable full-duplex audio communication, they often do not maximize the full capabilities of a system’s audio speakers. Because excess heat in a speaker’s voice coil and exceeding its excursion limit can cause rapid damage and cone blowing, audio engineers often impose hard limits on amplification levels that are well below the speaker’s actual capabilities. A software algorithm used in tandem with the amplifier monitors the temperature and excursion of the speakers in real time, and this feedback allows for finer sound pressure levels and higher audio clarity.

Voice Commands and Speech Recognition

Future video doorbells may enable hands-free control based on voice activation and voice recognition technology. Another layer of complexity is added when these voice user interfaces again receive commands from a series of microphones and DSP algorithms. Despite the relatively large distance from the receiving microphone, these doorbells will likely use beamforming algorithms to separate the desired audio signal from background noise. There are already available microphone boards that implement beamforming algorithms that amplify the speech signal from the direction of the speaker for clear speech and audio from noisy environments.

In a truly functional video doorbell product, it is important that these advanced features do not require additional power and can act on the local microphone input signal. We are looking for a design strategy to make the product simpler, low power and small size.

Power Budget Challenge

A practical video doorbell can be powered in one of the following ways: using a rechargeable battery, allowing it to draw power from the house’s existing low-voltage doorbell wiring, or equipping it with a Power-over-Ethernet (PoE) interface. Each of these power options has pros and cons (Table 1). As mentioned earlier, the flexible placement offered by the battery powered unit makes installation easier, while the doorbell cord has the advantage of low maintenance costs.

Power saving is a major concern for battery powered video doorbells, and many of the above algorithms will require more power-intensive processing. Highly specific SoC designs, such as the Texas Instruments (TI) CC3120/CC3220, enable higher levels of parallel processing (wake/sleep triggers, network connectivity) with fewer off-chip transactions (on-chip RAM and/or flash memory), Thereby reducing the total power consumption of the system. Additionally, MCUs designed for battery operation feature multiple power modes, including shutdown, hibernate, sleep, standby and active modes, which can be used by careful developers to further reduce energy consumption.

A major consideration for any product designed to use a home’s existing doorbell power supply is that there is no standard output voltage for these products in AC power supplies, which were originally designed to power bells using voltages between 8 V and 24 V AC. Designed. To minimize product degradation, it is important to pay careful attention to parameters such as output voltage accuracy, voltage ripple, system efficiency at full load, and heat dissipation. This is especially true for particularly sensitive components, such as CMOS image sensors often used in video doorbells. These components are particularly sensitive to noise sources such as power supply fluctuations, electromagnetic interference and temperature changes.

For optimal performance, a video doorbell needs a power supply that can accept a variety of low-voltage converters and produce clean, well-regulated voltages for its various subsystems (sensors, I/O, audio, memory, UI, etc.) Direct current, also has to be miniaturized to fit into a compact enclosure. As shown in Figure 3, this typically involves multiple buck converters, preferably synchronous buck converters that provide high efficiency under heavy loads. In such designs that require a wide voltage range or a large number of discrete power supplies, a single buck regulator can be used to power multiple linear regulators.

Figure 3: Schematic diagram of video doorbell power supply architecture

System efficiency at full and light loads is required for battery powered applications, as well as for products operating in closed packages with little or no ventilation. For video doorbells, features such as user interface, wireless communication monitoring, and motion detection must be carefully implemented to maximize power efficiency. The same attention must be paid to standby currents, such as the quiescent and shutdown currents of the power supply, as they can significantly affect battery life. Low quiescent current can greatly extend battery life as the video doorbell spends most of its time in sleep/hibernate mode. In addition, the synchronous converter has a seamless transition from its PWM mode to power saving mode, allowing it to remain relatively efficient at both full and light loads.

Video doorbells are one of several IoT products that have strict size constraints (and sometimes power constraints) and must balance processor-intensive algorithms with limited power resources. These limitations lead to some unique design challenges that are now made possible by technological advances. Naturally, these challenges will continue to become increasingly complex as artificial intelligence in the form of voice, voice and facial recognition becomes a must-have feature in residential security systems.

By Srinivasan Iyer, Systems Engineer in the Building Automation Division of Texas Instruments (TI), specializing in video surveillance, HVAC, elevators and escalators, among other industries.

The Links:   NL12876BC15-01 FP40R12KT3

FAVAC Virtual Showroom Goes Live: A Comprehensive Showcase of Leak Detection Solutions for the Pharmaceutical Industry

Pfeiffer Vacuum officially launched a new virtual exhibition hall, which comprehensively displays different types of drug packaging leak detection methods (Container Sealing Integrity Test, CCIT for short) through diversified representations such as pictures, texts and videos. With just one click, visitors can learn online about the challenges faced by the pharmaceutical industry when it comes to leak testing non-porous primary packaging, including infusion bags, syringes, blisters, plastic bottles and vials, and more. In addition, through the virtual booth on the website, visitors can learn about Pfeiffer Vacuum’s professional leak detector product portfolio and gain an intuitive insight into the technical means they use through video demonstrations.

It is well known that a durable and reliable seal is a must for pharmaceutical primary packaging. The ingress of humidity, oxygen or microorganisms can seriously impair the quality of the drug product during the shelf life of the product. Drugs that are particularly moisture sensitive (such as dry powder inhalers) can lose stability if the seal is insufficient, or can lead to contamination of parenteral drugs with biomass. To avoid such risks, high sensitivity integrity of drug packaging Testing is critical.

Pfeiffer Vacuum offers a wide range of leak testing methods for different process steps, packaging types and drug types with professional, reliable and sensitive leak detection technology to solve the many challenges facing the pharmaceutical industry.

In the virtual booth of the online exhibition hall, Pfeiffer Vacuum vividly and intuitively demonstrated various leak detection technologies to visitors through video, including helium mass spectrometry, emission spectroscopy and mass extraction (Mass Extraction). A unique portfolio of leak detectors for three CCIT technologies and how these products provide assurance of achievable detection limits and cycle times for packaging. In addition to demonstrating leak detection methods for pharmaceutical packaging, there are more details in the showroom about individual feasibility studies in the laboratory. In such studies, experts from Pfeiffer Vacuum present suitable CCIT applications for the specific packaging situation.

Caption: Pfeiffer Vacuum CCIT Virtual Showroom

The Links:   EVL32-060D CR6L-250/UL

Only by understanding the principle of the human brain can we create a brain-like computing system Tianji chip

Brain-like computing is a new computing technology based on the development of neuromorphic engineering, drawing on the basic principles of brain science, artificial-oriented general intelligence.

Why develop such a technology? Now human beings live in a digital universe, where everything is connected anytime, anywhere, forming a digital universe where everything is interconnected. This universe is growing very fast, information is doubling every two years, the entire universe is expanding rapidly, and it never regresses, and such a universe is based on our current computer architecture, which in turn is based on the von Neumann architecture.

The Von Neumann architecture is in my opinion the most concise, beautiful and most influential architecture in the history of human development. It is characterized by the separation of computing and storage, and the computing and storage are scheduled back and forth through the bus. It can be imagined that the round-trip scheduling consumes a lot of energy, delays time, slows down, and causes congestion, so there is a bandwidth bottleneck.

2017 Turing Award winner John L. Hennessy and David A. Patterson recently wrote a long article that concluded that the next 10 years will be a golden decade for computing architecture. The main reason is that in the past we used computers to do calculations, and now we use them to process information, but the digital universe is doubling every two years and all the energy consumption is unbearable.

Of course, there are other reasons, that is, we are now living in an era of artificial intelligence, and artificial intelligence has made great achievements. Although AlphaGo defeated the world champion of Go, artificial intelligence still has many bottlenecks. In short, the development of artificial intelligence 5 conditions must be met:

1. Sufficient data. 2. The decisive question. 3. Complete knowledge. 4. Static. 5. A single system.

For example, if you let an intelligent robot go to a destination autonomously, it cannot be done without programming it in advance. It took us a few years to establish this concept: where, how to get out, go through the door, go through the window , all of which are related to general intelligence, so our conclusion is: to develop an artificial general intelligence.

To develop artificial general intelligence, we must learn from the brain, which is currently the only general intelligence in the entire universe. Comparing the human brain with a computer, although the principles of the two systems are different, they have a strong complementary effect.

Therefore, the current computer system can be transformed by borrowing the basic principles of brain science. Developing brain-like computing is a very important part of developing artificial general intelligence, because it is the cornerstone of computing.

The development of artificial general intelligence is not a recent idea. If we look at the early articles of great scientists such as Turing and von Neumann, it is not difficult to find that this is the dream of scientists for a long time.

Why is now the best time to develop artificial general intelligence? Because with the development of sophisticated instruments, humans have learned more and more about the brain, and now it seems that we have reached a critical point in understanding the brain. The development of supercomputers can help scientists to do excellent simulations. Big data and cloud computing that save money, effort and time provide scientists with a system as complex as the brain, echoing the brain, so that we can work together. research and mutual promotion.

In addition, with the development of nanodevices, scientists can develop Electronic devices, and the energy consumption can reach the level of neurons and synapses in the human brain, so now is the best time to develop artificial general intelligence.

The development of brain-like computing to support artificial general intelligence plays a very important role in the brain. What role does it play?

Thirteen years ago, I felt that Moore’s Law would come to an end in 20 or 30 years, so I started the research on brain-like computing. Although I thought that my research was not bad, in terms of brain-like computing, I suddenly felt myself. I don’t know how to do research anymore, because there is no literature in this field, and many things need to be explored by myself, so I feel very distressed.

Once I went to climb a mountain and deliberately let myself get into the forest, no accident, I got lost. Later, I judged the direction according to the sun, stared in one direction and kept walking, walking, walking all the way to the highway, and stopped a car. Another time, I entered the forest on a cloudy day and got lost, so I thought of a way: keep climbing to the top, climb to the highest point, keep walking, keep walking, and finally reach the highway On the road, I stopped a car and went home.

Through these two things, I began to think, the brain plays the role of a compass and provides me with a sense of direction.

When doing scientific research, I like to choose fields that are more difficult to do, because I think the harder it is to do, the easier it is, because there are many competitors in the fields that are too easy, and it is difficult to lead. If it is a more difficult field, if you are doing it, no one else will do it, and you can lead, but there is a precondition: the direction must be correct. If you go on the wrong road, it will be very embarrassing.

Human intelligence is based on carbon, and we have built the current digital universe on silicon, and carbon and silicon have very similar structures, so we have a belief that what can be achieved on carbon can be achieved on silicon. Basically, it must be possible.

Discipline distribution: Challenges in developing brain-like computing and artificial general intelligence

The real challenge for developing brain-like computing and artificial general intelligence is neither science nor technology, but our disciplinary distribution. The current disciplinary distribution makes us do not have suitable people to do this research, and brain science and computer science are one Primarily exploring the natural world, the latter focuses more on applications. These two fields have different cultures, languages, and different goals, so multidisciplinary integration is especially critical.

The Brain-inspired Computing Research Center of Tsinghua University consists of 7 departments, because this field is not only the integration of computer and brain science, but also the integration of mathematics, physics, electronics, microelectronics, etc.

Teachers from our 7 departments discussed repeatedly, half a day a week, and finally we only did one thing for 7 years, called integration, integration and integration.

In this process, we have sorted out how to develop artificial general intelligence. There are two main routes: first, computer-led; second, brain science-led. Computer-led like machine learning, it has achieved brilliant results in image recognition, speech understanding, and natural language processing, but it is difficult to deal with uncertainties and so on.

Neuromorphic computing in brain science is also developing rapidly, but because we do not understand the mechanism of the brain, it has greatly hindered its development, but the two technical routes are actually complementary, and the combination of the two is currently the best in our opinion. a way.

There are actually two more to develop brain-like science: 1. Based on computers, use the basic principles of brain science to change the computing architecture; 2. We use a simple and clear word like “brain-like” to cover these two parts.

How can a brain-like computing system be built without understanding the principles of the human brain?

In this research, you actually need to study theories, chips, software, systems, cloud brains and applications. However, everyone always asks a question: If you don’t understand the human brain, how can you create a brain-like computing system?

We thought about it for a long time, and then we got the answer. The answer is this: the computer converts the information in the multi-dimensional space into a one-dimensional information flow such as 0 and 1, and uses the calculation to solve the problem. The main frequency of the CPU is getting faster and faster. In other words, you are using the time complexity. The problem is that when you reduce the dimension, the correlation is lost. This is that it is easy for people to determine whether an object is in real space or in In the mirror, but it’s hard for a computer, and that’s the root cause.

For the brain, we don’t know its basic principle, but we know that a neuron connects one thousand to ten thousand neurons. In other words, we expand the information in this place and enhance the correlation. We use the is the space complexity. In addition, the brain also uses pulses for coding, which introduces the factor of time, and we also take advantage of the complexity of space and time. Therefore, we want to maintain all the advantages of the current computer and maintain the time complexity to add a brain-like chip.

What is added? The increase is the space complexity, time and space complexity. If we look at current technology from this point of view, you will find that today’s artificial, neural network accelerators are geared towards deep artificial neural networks. It uses space complexity, and neuromorphic computing, which works like a brain, is oriented to spiking neural networks. It uses space-time complexity, a space-time complexity, a space-time complexity, why not combine it?

Therefore, we propose the Tianji chip architecture, which supports both artificial neural networks and spiking neural networks that work like brains at a cost of 3%, and also supports two heterogeneous modeling. We also use brain-like chips to build a research platform for artificial general intelligence.

Our idea is to build a multi-modal cross-research platform that can interact with the system. We use environmental changes to force the system to change. When it changes, we observe the basic principles that the system should follow to apply this change. Help us iterative development, using a Tianji chip, we can realize perception, tracking, obstacle crossing, obstacle avoidance, automatic control, voice understanding, and autonomous decision-making.

The chip is very important, and the software is also very important, because if there is no software, application engineers are reluctant to do application software development. So we developed a software tool chain ourselves, and in our lab, we have actually built the first generation of brain-like computers.

What we are doing now is a brain-like cloud brain. The difference between it and the current cloud computing is that cloud computing integrates many technologies, while the brain-like cloud brain is oriented to artificial general intelligence, because the research of artificial general intelligence is basically different from many artificial intelligence. Stacked together, our idea is to combine the elasticity of the brain with the rigidity of the computer, data-driven and knowledge-driven, and general knowledge and reasoning.

Of course, this is a very challenging long-term research, and our strategy is to proceed step-by-step. It can be imagined that we first focus on the research of one problem, which can be called the first generation, and then study the two problems together. This can be called the second generation, then the third generation, the fourth generation, and finally the fifth generation, so that we can build artificial general intelligence.

Artificial General Intelligence: Empowering All Industries

We develop brain-like computing and support artificial general intelligence. Because it is general intelligence, it can empower all walks of life and have many applications.

We are particularly interested in intelligent education, and many problems in current education can be solved through this research. For example, high-quality educational resources are scarce, resulting in inequity in education. Due to limited funds and limited equipment, it is difficult for us to truly connect theory with practice.

With the development of brain-like computing and artificial general intelligence, these will be gradually solved, and then new systems will be developed. But there is another very important factor, because education is primarily about shaping people.

Since the Industrial Revolution, human beings have developed steam engines, generators, computers, big data, and now the Internet of Everything. Humans have been changing the external world and our material life. When our material life has developed rapidly, our spiritual life has not actually developed synchronously. We are now developing brain-like computing in the age of intelligence, so that we have the opportunity to develop inward and examine our hearts.

I sincerely hope that while developing our technology and exploring the outside world, human beings can also study our inner world, cultivate both inside and outside, and develop together, so as to build a beautiful and harmonious world!

Author: Shi Luping

The Links:   DFA100BA160 LQ9D340H

With the acceleration of urban digitalization, how does AI overcome the problem of long-tail scenarios?

In most sci-fi films, the forms of future cities have several commonalities: people can interact with all public facilities, visualization of public transportation data, real-time data transmission over long distances between people and people, and highly intelligent community and building control.

The ultimate goal of smart cities is also the same. Everything, including people, can be freely interconnected, all information is transmitted using data as a carrier, and any problems and needs can be solved through data collection and analysis. According to the above settings, the current smart city development is still at a very early stage, but the society’s pursuit of urban digitalization has been accelerating.

At the beginning of this year, Shanghai officially released the “Opinions on Comprehensively Promoting the Digital Transformation of Shanghai City”. This year’s Shanghai government work report also pointed out that in 2021, Shanghai will promote digital industrialization and industrial digitization, and accelerate the development of a new online economy. According to the “White Paper on the Development of China’s Digital Economy (2021)”, the scale of the domestic digital economy was 39.2 trillion yuan last year, accounting for 38.6% of GDP, and the growth rate was more than three times faster than GDP. There is no doubt that a thriving digital economy has become the key to driving sustained and long-term economic growth.

Now, urban digitization is gradually moving from point and line to surface dimension, showing stronger integration, and the direct effect of integration is the exponential improvement of operational and governance efficiency requirements, as well as the general adaptation of scenarios. In fact, this is still a matter of AI technology and layout, such as the amount of computing power, the precision of the algorithm, the fault tolerance rate and scheduling ability of the platform, etc. These projects involve long-tailed urban governance scenarios such as bicycle parking and garbage exposure, which often require all-weather and high-precision management and control. Therefore, the AI ​​systems of participating companies will also be affected in terms of visual recognition, rapid judgment, and timely response capabilities. put forward more stringent requirements. Urban governance is eager for “high-speed efficiency” According to the National Bureau of Statistics, the urbanization rate of my country’s permanent population has exceeded 60% in 2020.

Population increase and agglomeration have brought greater pressure on urban governance. Coupled with some governance problems brought about by the development of the new economic model based on sharing, the difficulty of urban governance is actually increasing. There are also some typical livelihood problems, such as high-altitude parabola, motorcycles entering elevators, and reasonable garbage classification. The superposition of these long-tail scenarios also brings new challenges to urban governance, especially in governance efficiency and resources.

Traditional digital governance methods have been difficult to adapt to these complex long-tail scenarios. On the one hand, traditional methods are mainly based on simple dataization, and do not form a complete closed-loop logic and solution with offline governance. On the other hand, because traditional methods are intelligent The degree is low and cannot meet the requirements of large-scale and multi-scenario. For example, in traffic travel, traditional visual solutions can only store, record, photograph, and identify common behaviors that need to be managed and controlled, but cannot judge and respond to abnormal events such as traffic jams and random parking. On-site management.

Another example is the focus of social and livelihood issues such as motorcycles entering elevators. Traditional visual solutions often do not have the ability to recognize. Even the intelligent solutions given by some companies have obvious shortcomings in recognition accuracy and post-recognition response. . Complicated long-tail scenarios and high-frequency visual analysis, from the perspective of AI technology, are actually a matter of computing power and algorithms. With a large scale and more requirements, the computing power must be strong enough to process and analyze these huge dynamics. The data and algorithms must also be matched, so that they can be analyzed and processed quickly and accurately. In general, as the number of scenes accommodated by the objective environment increases, the differences between the scenes increase, and the difficulty of urban digital governance increases accordingly, which puts forward higher requirements for efficiency and accuracy.

Hard solution of AI ecology Since the objective requirements of urban digital governance have become higher, only stronger AI solutions can be adapted accordingly. In fact, there are also two problem-solving ideas here. One is to overcome single scenarios one by one, but the ultimate unified management is realized. The difficulty is high. The other is to establish a basic solution first, and then superimpose and adjust it according to different scenarios, which requires the foundation to be hard enough. At the 2021 World Artificial Intelligence Conference, SenseTime released a blockbuster product called “SenseCore AI Big Device”, which is positioned as an AI infrastructure that can solve enterprise services, urban management, personal All kinds of long-tail application problems of life.

Although it is infrastructure, this big AI device is divided into three layers of computing power, platform, and algorithm, and each layer has different functions and capabilities. For example, in terms of computing power, SenseTime has established Asia’s largest artificial intelligence computing power center in Shanghai. In terms of algorithms, it provides enterprises with personalized algorithm tools based on the model output from the platform layer. So far, more than 17,000 algorithm models have been developed.

The foundation of strong computing power, coupled with the continuous iterative algorithm blessing, is also a relatively unified development idea for the AI ​​and cloud computing tracks, but the differentiated competitiveness of each product is precisely because of this. Without platform-based collaborative integration, the overall efficiency, flexibility, and cost will be greatly reduced.

As far as the specific application is concerned, the core value of SenseTime’s large-scale device logic is that it can output different and useful solutions based on the same system. For example, Ark City Development Platform, in which SenseFoundry Traffic (Shangtang Ruitu) covers the three scenarios of rail traffic, traffic management and high-speed, and can make intelligent identification and rapid decision-making according to the needs of different scenarios; The solution, through the integration of perception, vision, and data capabilities, can perform digital and intelligent empowerment for scenarios such as parks, production, and emergency.

The difficulty of urban digitization lies not only in the scale of the scene, but also in the dimension of the scene. For example, compared with the individual level, enterprise-level digitization often requires the ability to penetrate the entire industry chain or the entire scene. Therefore, on the basis of a set of systems, to Effectively covering all scenarios, obviously requires the system to have strong compatibility and classification processing capabilities, as well as platform-based functional attributes.

The solution to the long tail problem For city managers, solving all problems with one system is the ultimate perfect solution, because it has high efficiency, low cost and good effect. Especially in various long-tail scenarios that are currently more prominent, if there is a system that can manage these scenarios in a unified manner, the governance efficiency will be amazingly improved. In fact, the goal of AI industry development is also the same. AI+ enterprises and industries are a set of logic to meet all needs and solve all problems. Now we have seen many unified enabling products in the fields of industry and agriculture, which is also the continuous fermentation of this trend. Where is the advantage of such a methodology, the application results of SenseCore AI big device can give some reference.

During the pilot period of “AI + One-Network Unified Management” in Changning District, Shanghai, more than half of the incidents were handled within 4 hours, and the fastest only took 20 minutes. In elevator-related scenarios, the escalator safety intelligent response system jointly built by SenseTime and Schindler last year can dissuade unsafe behaviors by voice at the entrance and issue early warnings at the exit based on the density of people; the wisdom jointly created by SenseTime and Evergrande The community can effectively identify unsafe behaviors such as motorcycles entering elevators and high-altitude parabolic objects. It can be seen that with the help of AI, the processing of long-tail scene problems has been significantly improved in two aspects, one is higher efficiency, and the other is a wider processing range. The existence of these long-tail scenarios is characterized by high repetition, that is, the processing logic and needs of different communities and cities are the same, and the processing of single or regional scenarios can obviously be effectively and quickly replicated and promoted. However, it should be noted that although the processing logic of the long-tail scenario problem is the same, the massive data that can be superimposed will also bring certain challenges to the computing power and algorithms.

In the long run, the core of the long-tail scenario problem is actually the efficiency and accuracy of AI judgment. Although the occurrence of critical point behaviors in the scene may be low-frequency, AI must conduct high-frequency analysis and judgment in order to prevent small and gradual progress. Not a patchwork. Smart cities are inseparable from a high-quality AI base. More cities accelerate the objective background of digital reform. In fact, it is the improvement of AI industrialization capabilities. In the early years, AI technology was still code. The process from 0 to 1 did not depend on the application depth and breadth, but now it is different. The co-evolution of AI, big data, cloud computing, Internet of Things, 5G and other technologies is giving AI applications. Open a superspace.

AI is a new infrastructure, just like the Internet in the past, it will eventually be added to all industries, but it is much more valuable than the Internet. AI can become the strongest productivity factor, driving the upgrading of the industry’s production methods and production logic, and ultimately the unit Produce more and better.

The SenseCore AI installation is such an infrastructure facility. For cities, its significance is not only to provide better digital solutions in the three areas of governance, industry and life, but also to provide cities with a comprehensive digitalization and life. Intelligence has created an extremely solid and inclusive urban base. On this urban base, seamless and efficient interconnection of all things will be easier and faster to achieve. But no matter how powerful this infrastructure is, AI must not cross the moral and ethical boundaries. Inclusiveness is the ultimate goal pursued by all technologies, but technology always serves people and cannot put the cart before the horse. Therefore, AI ethical governance is to identify and master this degree determined by people.

At WAIC 2021, Xu Li, the co-founder and CEO of SenseTime, mentioned that SenseTime will be committed to a balanced ethical governance standard of safe and controllable technology, people-oriented, and sustainable development, and advocated that the industry should uphold the “development” of artificial intelligence ethics.

The future direction of urban digitalization is very clear, that is, to continuously improve the quality of management and the breadth of management. In this process, the industry needs professional players such as SenseTime who have established a solid infrastructure in urban digitization, because the AI ​​technology ideas of such players have never left the specific real scene, and the solutions are also suitable Scenario needs, and the ethical standards of technology will be considered, which is the key to urban digitalization can be defined as high quality.

The Links:   LTM10C273 PT76S16

Huawei Hongmeng VS Google Fuchsia, who has a better chance of winning?

Huawei’s Hongmeng system is about to be launched, and Google is not sitting. Foreign media reports that Google has teamed up with Samsung to test Fuchsia OS, which seems to be aimed at sniping the Hongmeng system. It can also be seen that Google attaches great importance to the Hongmeng system.

Hongmeng and Fuchsia are rivals

Huawei’s Hongmeng system adopts a distributed architecture, and can support devices in various industries such as tablet computers, mobile phones, PCs, and home appliances by adding different modules. It can be said that it has great expectations for the Hongmeng system from the beginning.

Google’s Android system is the largest operating system in the mobile market. It is currently used in tablets, mobile phones, wearables and other devices. It has also developed the Chrome OS system for laptops. However, Chromebooks equipped with Chrome OS have always been in the United States. The large market share of the education market did not further erode the PC market.

Google has long recognized the importance of a unified operating system, so it launched Fuchsia OS in 2016, hoping to unify multiple industries such as tablets, mobile phones, and PCs with Fuchsia OS. Fuchsia OS also adopts a distributed architecture similar to the Hongmeng system, and can also support many devices by adding modules.

Perhaps in order to continue the leading edge of the Android system in the mobile market and continue the ecology of the Android system, Fuchsia OS is written using the Flutter SDK that can run on Android, so Fuchsia OS is expected to run on many current Android devices.

At the moment when Huawei is launching the Hongmeng system with great fanfare, Google and Samsung test Fuchsia OS, which makes people think that the latter two have the meaning of sniping at Huawei Hongmeng.

Hongmeng or Fuchsia who has a better chance of winning

Huawei emphasizes that it has reached cooperation with Midea and other home appliance companies. These home appliance companies will help the Hongmeng system to gain more users and further improve the ecosystem. However, at present, no domestic mobile phone company has publicly expressed its support for the Hongmeng system, but ZTE said it It has been developing its own mobile phone operating system so there is no plan to adopt the Hongmeng system.

It is understandable that domestic mobile phone companies did not explicitly support the Hongmeng system, because they currently occupy a large market share in overseas markets. Among them, overseas shipments of OPPO and vivo mobile phones account for nearly 50%, and overseas shipments of Xiaomi mobile phones. They account for nearly 70%, and they are worried that their cooperation with Huawei Hongmeng may be hit by Google.

The HMS service paired with the Hongmeng system is said to have more than 100,000 APPs, but this has obvious disadvantages compared with the millions of APPs in the Android system, especially due to the competition with Google, which has an advantage in the global market. Google search, Google Maps, YouTube and other applications cannot upload HMS, which is not conducive to Hongmeng going overseas; Fuchsia system can use Android’s ecology through compatibility with Android, which is a strong competitive advantage of Fuchsia.

Samsung, which has joined forces with Google, is the world’s largest mobile phone company. Samsung also provided a strong boost to the development of the Android system that year. The cooperation between the two parties can be described as a matter of course. For other Android mobile phone companies, especially Chinese mobile phone companies, they need Google’s support to go overseas. It is expected that Chinese mobile phone companies other than Huawei are likely to support Fuchsia.

Whether it is the system ecosystem or its partners, relying on the accumulated advantages of the Android system, Google Fuchsia, which continues the Android ecosystem, obviously has an absolute advantage, while Huawei Hongmeng seems to be a bit alone, and Google Fuchsia is obviously much more likely to win.

Of course, the fact that Chinese mobile phone companies do not explicitly support Huawei Hongmeng does not mean that they will not support it in the future. After all, Android mobile phone companies including Chinese mobile phone companies have been squeezed by Google Android in recent years, and Google has continued to tighten its control over Android. Even the gesture control developed by Android mobile phone companies is restricted, and more and more Google applications are inserted, which makes the Android system extremely bloated. Android phone companies are forced to be angry and dare not speak out because of Google’s power. If Huawei Hongmeng is good enough There is still a chance to get enterprise support for Android phones.

The Links:   NL6448BC20-18D 300UR120A

Learn how optimized chips will open up the small cell market from 7 aspects

In the diverse architecture of mobile networks, small cells are often considered as solutions that meet some limited requirements, and are often seen as part of a homogeneous product. But even in the field of small cells, there are many differences in features, functionality, and architecture. While small cells are just base stations that cover a small radius, their capabilities may include support for different frequency bands, number of users, and power consumption levels.

Author: Wang Zhengfang, Vice President of Engineering, Bicoc Microelectronics (Hangzhou) Co., Ltd.

Since the opening of the first commercial telegraph line in 1844, the global telecommunications industry has been showing the world the most advanced technological and economic progress, involving technological innovation, emerging businesses, economies of scale, service quality, interconnection (standardization), etc. It is inseparable from the latest technology, and it is also inseparable from accurate business calculation and design. With the large-scale deployment of 5G in the early stage and the continuous increase in penetration rate, the technical and economic evaluation of 5G communication services will enter a new stage. At the same time, operators have begun to invite tenders for the introduction of 5G small cells. However, the major technical and economic changes are still being promoted. It’s those little chips.

Below, we will introduce how optimized and innovative chips can change the deployment and operation of 5G from seven aspects.

1. Diversity in RAN is not just more vendor choices…

For a variety of reasons, carriers want to see more mobile device vendors to choose from. This means that most industry discussions about Open RAN focus on one outcome: increasing vendor diversity. Our industry will benefit from a greater diversity of RAN suppliers, but it will take much more than just seeing more supplier names in the supply chain. The distributed RAN architecture supports multiple deployment methods, helping to provide the best user experience.

2. We are seeing an increase in diversity on many levels…

Network and business needs are becoming increasingly diverse. To use new spectrum resources, devices must be flexible enough to support an ever-increasing range of frequency bands, from sub-GHz all the way to millimeter wave (mmWave), licensed to unlicensed, shared to dedicated, often in different countries /regions are presented in different combinations. Network equipment must also support different generations of mobile networks from 2G all the way to 5G. To profit from the deployment of 5G networks, operators aim to provide services with different latency and throughput requirements for different application scenarios.

To meet the demands of these use cases, they are faced with increasingly diverse deployment environments and capacity requirements, with indoor, dense urban, transportation networks, and rural and suburban all exhibiting vastly different coverage and cost configurations. Finally, the way mobile networks are funded, deployed, owned and operated is changing. With the emergence and growth of neutral third-party models, managed network-as-a-service, and private networks in unlicensed shared and dedicated spectrum, equipment vendors must recognize the need to be able to support a range of deployment architectures.

3. The small base station itself is diverse…

In the diverse architecture of mobile networks, small cells are often considered as solutions that meet some limited requirements, and are often seen as part of a homogeneous product. But even in the field of small cells, there are many differences in features, functionality, and architecture. While small cells are just base stations that cover a small radius, their capabilities may include support for different frequency bands, number of users, and power consumption levels.

Architectural diversity is related to how small cells implement functional division for RAN processing, and the associated fronthaul and backhaul requirements. There are also various deployment/operation methods of small cells, such as private private networks, neutral third-party deployments, or operator-deployed networks. 3GPP will not go into sleep mode, there will only be more features and requirements on the roadmap. Therefore, small cell developers need to take all these variables into account.

4. Diverse environments require efficient responses

Operators and their suppliers need to be able to meet these different requirements cost-effectively and efficiently. Operators need a RAN that matches the environment so that it can adapt to the needs of the surrounding environment. This means obtaining solutions suitable for different network architectures, deployment situations and different application scenarios. This also means relying on various optimized systems to support these solutions. It is impossible for developers to design different, end-to-end solutions for each instance, and it is impossible to use only one solution for various diverse needs.

5. Flexible chip solutions can provide answers…

The feedback Picocom has received is that commercially available chips are needed to enable more diverse solutions that can be tailored by equipment vendors based on service and deployment requirements. Our raison d’etre is to design something that builds as many permutations as possible on a single chip and still achieves the best cost point and low cost you’d expect from an optimized SoC approach power consumption.

6. The chip + software design can meet the task requirements…

We can achieve diversification multipliers by applying good semiconductor economics. We support new vendors to participate and design products based on architectures with suitable interfaces, enabling flexible solutions. Supporting higher or lower PHY splits is an example: we use the same chip to support higher or lower splits, differentiated by specific software. This provides system developers with a common platform that is flexible to meet the different needs of the industry.

7. RAN diversity can be real…here’s how.

Achieving RAN vendor diversity is currently a strategic driver for mobile network operators (MNOs). However, it must be based on a silicon solution that enables vendors to deliver optimized solutions at the right cost point and power consumption level. By supporting distributed and open architectures, flexible silicon solutions can achieve the ultimate goal of vendor diversity.

Picocom has built and will continue to provide optimized and flexible silicon and software solutions that enable operators to meet their diverse network needs and take advantage of a more diverse vendor market.

The Links:   LTM10C027 DF150AE160

The IPO of “The First Share of Car Cores” was suspended, and BYD pressed the pause button

In May of this year, BYD semiconductor‘s announcement of its listing has attracted great attention from the market and has become a strong candidate for the “first stock of car cores”. But a few days ago, its IPO listing review was suspended, and BYD was pressed the pause button.

BYD: Advance the review as soon as possible

On August 18, the Shenzhen Stock Exchange suspended the issuance and listing review of BYD Semiconductor Co., Ltd. (hereinafter referred to as “BYD Semiconductor”) because the issuer’s law firm was investigated by the China Securities Regulatory Commission. The law firm is Beijing Tianyuan Law Firm (hereinafter referred to as Tianyuan Law Firm).

According to regulatory requirements, BYD Semiconductor can only resume its application for listing after the relevant circumstances of Tianyuan Law Firm are eliminated, or after due diligence is completed within three months and the Shenzhen Stock Exchange is notified in a timely manner.

In response to this matter, BYD Semiconductor told the media, “The company will now push forward some review reports as soon as possible. As for whether it will change, we do not know.”

2.7 billion financing, the valuation exceeds 10 billion!

As early as 2020, BYD Semiconductor was about to be split and listed. BYD Microelectronics completed internal reorganization, changed its name to “BYD Semiconductor”, and plans to introduce strategic investors.

In the second quarter of 2020, BYD Semiconductor completed the A round and A+ round of financing respectively, with a total financing of 2.7 billion yuan. And this year announced a spin-off listing, with a valuation of 10.2 billion.

Vehicle-grade IGBT has been mass-produced, and it is the largest domestic manufacturer

It is reported that in the automotive field, BYD Semiconductor has mass-produced IGBTs, SiC devices, IPMs, MCUs, CMOS image sensors, electromagnetic sensors, LED light sources and displays;

In the fields of industry, home appliances, new energy and consumer electronics, IGBT, IPM, MCU, CMOS image sensors, embedded fingerprint sensors, electromagnetic sensors, power ICs, LED lighting and displays have been mass-produced.

BYD Semiconductor is the largest manufacturer of IDM automotive-grade IGBTs in China. Its automotive-grade IGBTs are the core components of new energy vehicle Electronic control, and have achieved mass production and vehicle application. At the same time, BYD is also the first semiconductor manufacturer in the world to apply SiC modules to the main electronic control of automobiles.

The Links:   EL640400-CB1 M150XN07-V5

A compact industrial controller for Ethernet has been developed

The concept of Industry 4.0 was first proposed by Germany in 2013. It is one of the top ten projects in the future. From its proposal to the present, it has attracted global attention and triggered a new round of industrial transformation competition on a global scale. It aims to improve the intelligence level of the manufacturing industry and build smart factories with adaptability, resource efficiency and genetic engineering. Its technical foundation is the network entity system and the Industrial Internet of Things.

Recently, maxon has developed the EPOS4 Compact positioning controller, ready to use for industrial Ethernet connections. maxon is a worldwide supplier of high-precision electric motors and drive systems. In high-precision motors and drive systems up to 500W, maxon is a global leader. The successfully developed EPOS4 Compact series of devices can be integrated into deterministic Industrial Ethernet (CAT), creating new opportunities for a variety of applications.

Ethernet control automation technology is an open-architecture, Ethernet-based fieldbus system, the purpose of which is to allow Ethernet to be used in automation applications.


Currently, the controller uses an additional programming language: the new deterministic Industrial Ethernet model is CoE compliant and can be easily integrated into existing deterministic Industrial Ethernet. The new smart motion controller with real-time communication provides a simple and convenient way of working to control brushed DC and brushless EC motors with peak currents up to 30A. Thanks to its modular design, it saves space and is especially suitable for single- or multi-axis systems in small plants and machines, as well as robotics. The space saved can be used for the design of other functions to improve machine performance. It can also be used in the field of miniaturization of robots and industrial equipment. Provide value for the development of the Fourth Industrial Revolution.

And maxon also offers its customers a wide range of accessories to make the connection and integration process as simple as possible. In addition to the intuitive “EPOS Studio” software, the controller can integrate Windows DLLs and Linux shared object libraries into various host systems free of charge. The space-saving, compact positioning design of the EPOS4 controller has gained many admirers in the control LAN world. The multifunctional EtherCAT controller is now available in two power versions: 50V/8A and 50V/15A.

The Links:   MK300A/1600V EW32F62BCW