The rise of smart machines is changing the world

Have you tried using a smartphone to "call" a car out of a parking space? Did you know that many fine surgical procedures are now done by robotic arm? Have you heard that drones can automatically track GPS flight routes and land safely without any damage?

At present, robots have even become as small as vacuum cleaners, as large as part of education or information electronics.

In fact, the amazing development of semiconductor technology has led to the renaissance of autonomous machines and artificial intelligence. At present, machines are increasingly performing tasks that were previously only possible for humans to complete, and the impact of this transformation on the entire world is expected.

The re-emergence of smart machines, especially drones, robots and semi-autonomous vehicles, has evolved from new things into countless commercial and industrial applications. The number of electronic components included in these machines has grown rapidly, enabling many new features, such as high-precision control and environmental recognition, that is, the comprehensive identification of a person's surroundings without physical proximity or special requirements for such information. . Previous generations of industrial robots or queued vehicles were almost always scheduled to perform high-precision repetitive operations. Modern autonomous machines have very distinctive features, including interaction with humans, the ability to handle emergencies, and the ability to learn quickly. All of these features require stronger environmental identification, greater intelligence, and greater control to support the back.

Two applications specifically for artificial intelligence include monitoring and control. Monitoring applications are typically responsible for processing big data generated by the Internet or a large number of sensors. Data mining and pattern recognition for large and ever-increasing amounts of data requires extremely high processing power for servers and processors. Numerous applications, such as security, medical diagnostics, and marketing, rely on data analysis and deep learning technologies. On the other hand, control applications require real-time analysis of sensor data and autonomous control of brakes and motors. Autonomous vehicles, drones and new generation robots are all classified as this category.

Ahmad Bahai, chief technology officer of Texas Instruments (TI), said that the three enabling technologies have contributed to the re-emergence of this smart machine:

1. Sensing: Due to advances in semiconductor and microelectromechanical systems (MEMS) technology, the price of a wide range of environmentally recognized and visual sensors deployed in autonomous systems has become affordable. While vision sensors such as cameras, radar, and LIDAR are critical to many autonomous systems, other environmental sensors that require lower processing power are more common. High-precision torque, temperature and magnetic sensor fusion provide rich tactile, proximity and ambient information; this enables robots to interact with humans and handle emergencies safely and efficiently. This is similar to many biological systems in humans and animals, they can respond to hardness, heat and magnetic field strength, and have many other non-visual sensing capabilities.

Based on these sensing technologies, visual analysis has naturally become the mainstream technology, because algorithms and processors are becoming more and more powerful, and prices are becoming more and more close to the people. Machine vision has long been used in industrial and consumer applications (such as gaming consoles), but the mission-critical nature of autonomous systems requires higher performance and higher reliability machine vision. Because of this, we can now see a large number of high-resolution cameras for applications in cars, robots and drones. These autonomous systems are taking advantage of advances in vision algorithms and stereo camera technology, and these cameras have advanced processors for depth detection and fusion.

Fully integrated complementary metal-oxide-semiconductor (CMOS) radar with a 250-meter extension range and precision of a few microns (usually these two specifications cannot be implemented simultaneously) when optical vision is unavailable or impossible (such as in heavy rain, snow or When driving in the fog, it can effectively complement the camera function. LIDAR is able to provide a more detailed map around the machine in real time with the help of a highly focused laser beam.

2. Processing power: The emergence of powerful processing capabilities, along with advanced neural network algorithms, has made significant contributions to machine vision efficiency and high reliability, pattern recognition and machine learning capabilities. A broad portfolio of graphics processing units (GPUs), bionic processors, and multicore ultra-long instruction word digital signal processors (VLIW DSPs) has enabled a wide range of vision subsystems. With a large number of auxiliary accelerators, the Treaflops Super GPU for deep learning and image processing is the key to the Composite Advanced Driver Assistance System (ADAS). However, many autonomous systems are battery powered, have limited processing energy budgets, and require energy efficient processing. High-performance multicore DSPs are equipped with accelerators for machine learning algorithms that provide the energy-efficient processing power they need for systems such as mobile robots and drones. A typical multi-core DSP, such as the TI C7X, offers lower power consumption, less bill of materials (BOM) processing, and higher scalability.

3. Motor and brake control: The motor has replaced many hydraulic and mechanical systems in the autonomous machine. The increased efficiency of motors and intelligent motor drives has helped robots and drones achieve high-precision motion. While electric vehicles take advantage of the higher efficiency of inductive AC motors and drives, many light robots and drones still use brushless DC motors to achieve the high efficiency and zero maintenance they require. TI's broad portfolio of gate drivers, such as the DRV8X family, offers intelligent gate drive capability and high integration for performance optimization and compact board design. Motors with integrated sensors, fault diagnostics and intelligent power management are critical for high precision and high torque applications in autonomous systems.

Despite technical and other challenges, smart machines are playing an increasingly important role in our daily lives. Their transformation from new things to everyday use is slowly emerging. Rapid advances in electronics and innovative applications show that the rise of smart systems will continue. A new generation of autonomous machines will provide us with an effective solution, let us welcome it!

Mechanical Timer

24 hours mechanical Timer
Instant indicator
Min.setting time:15 minutes. Max.setting timer:24 hours
With hand switch,can be switched to operating and

setting at any time

Instructions:

1. Set program: 1 pin is equivalent to 15 minutes. Determine desired start time and push down pins until desired
off time.
For instance, if you want electrical devices to work from 8:00am to 11:00am and from 13:00pm to 17:00pm, you
just need to put down allthe pins between the three period time.
2. Set the current time: Turning the dial clockwise until the arrow pointing to
current time.
For example,if now it is 8:00 am, please turn the dial and make sure the
arrow point to 8. (See the picture.)
3. Plug the electrical device directly into the timer. Make sure the electrical
device is power-on.
4. Plug the timer into electrical outlet and the electrical device will be work
according to the setting program.
Note: = Normal Ope n = Timing
Make sure the switch on the Timing position. If it
is on the [Normal Open" mode, the electrical device is
always power-on and the timer function no work.

Specifications:

Caution:
1.D o not exceed the maximum ratings of the timer.
2.M ust reset the current time after power failure.
3.D o not plug the timer directly into the working electrical appliances.
4.U nless changing the setting, keep the program same every day.
5.D o not disassemble timer by yourself. Professionals service are needed for maintenance.

6.T his item is only for indoor use.

Mechanical Timer, mechanical timer socket, 24hr mechanical timer, mechanical timer plug, mechanical timer adaptor

NINGBO COWELL ELECTRONICS & TECHNOLOGY CO., LTD , https://www.cowellsocket.com