About Rik

Myself Rik and I am founder of Riktronics. I study Electronics and Communication Engineering in IIE. My hobby is playing with electronics and making various projects, mainly about embedded systems. Love to do coding, and making tutorials about electronics/programming. Contact me in any need at abhra0897@gmail.com My blog : riktronics.wordpress.com

Researchers Developed New Efficient, Thin, and Flexible Cooling Device

Engineers and scientists from the UCLA Henry Samueli School of Engineering and Applied Science and SRI International, California, have created a thin flexible device that could keep smartphones and laptop computers cool and prevent overheating. The component is based on the electrocaloric effect – a phenomenon where the temperature of material changes when an electric field is applied to it. The research has been published in Science.

Thin, flexible cooling device
Thin, flexible cooling device

The system’s flexibility also allows it to be used in wearable electronics, robotic systems, and new types of personalized cooling systems. It is the first demonstration of a solid-state cooling device based on the electrocaloric effect. The method devised by UCLA and SRI researchers is very energy-efficient. It uses a thin polymer film that transfers heat from the heat source – a battery or a processor – to a heat sink, and alternates contact between the two by switching on and off the electric voltage.

Because the polymer film is very flexible, the system can be used in devices with complex shapes or moving surfaces. Body tracking wearable devices can easily accommodate this flexible cooling device. Such cooling pad could keep a person comfortable in a hot office and thus lower the electricity consumption for air conditioning. Or it could be placed in a shoe to keep a runner comfortable while running in the sun. It’s like a personal air conditioner.

The tendency of flexible electronics to overheat remains a major challenge for engineers. The cooling systems in larger devices like air conditioners and refrigerators, which use vapor compression, are just too large for mobile electronics. The new cooling device produces a specific cooling power of 2.8 watts per gram and a COP of 13. This is more efficient and compact than the existing surface-mountable solid-state cooling technologies, opening a path to using the technology for a variety of practical applications.

Roy Kornbluh, an SRI research engineer, said,

The development of practical efficient cooling systems that do not use chemical coolants that are potent greenhouse gases is becoming even more important as developing nations increase their use of air conditioning.

Get Sensor Data From Arduino To Smartphone Via Bluetooth

Hariharan Mathavan at allaboutcircuits.com designed a project on using Bluetooth to communicate with an Arduino. Bluetooth is one of the most popular wireless communication technologies because of its low power consumption, low cost and a light stack but provides a good range. In this project, data from a DHT-11 sensor is collected by an Arduino and then transmitted to a smartphone via Bluetooth.

Required Parts

  • An Arduino. Any model can be used, but all code and schematics in this article will be for the Uno.
  • An Android Smartphone that has Bluetooth.
  • HC-05 Bluetooth Module
  • Android Studio (To develop the required Android app)
  • USB cable for programming and powering the Arduino
  • DHT-11 temperature and humidity sensor

Connecting The Bluetooth Module

To use the HC-05 Bluetooth module, simply connect the VCC to the 5V output on the Arduino, GND to Ground, RX to TX pin of the Arduino, and TX to RX pin of the Arduino. If the module is being used for the first time, you’ll want to change the name, passcode etc. To do this the module should be set to command mode. Connect the Key pin to any pin on the Arduino and set it to high to allow the module to be programmed.

Circuit to connect HC-05 with Arduino
Circuit to connect HC-05 with Arduino

To program the module, a set of commands known as AT commands are used. Here are some of them:

AT Check connection status.
AT+NAME =”ModuleName” Set a name for the device
AT+ADDR Check MAC Address
AT+UART Check Baudrate
AT+UART=”9600″ Sets Baudrate to 9600
AT+PSWD Check Default Passcode
AT+PSWD=”1234″ Sets Passcode to 1234

The Arduino code to send data using Bluetooth module:

//If youre not using a BTBee connect set the pin connected to the KEY pin high
#include <SoftwareSerial.h>
SoftwareSerial BTSerial(4,5); 
void setup() {
 String setName = String("AT+NAME=MyBTBee\r\n"); //Setting name as 'MyBTBee'
 Serial.begin(9600);
 BTSerial.begin(38400);
 BTSerial.print("AT\r\n"); //Check Status
 delay(500);
 while (BTSerial.available()) {
 Serial.write(BTSerial.read());
 }
 BTSerial.print(setName); //Send Command to change the name
 delay(500);
 while (BTSerial.available()) {
 Serial.write(BTSerial.read());
 }}
void loop() {}

Connecting The DHT-11 Sensor

To use the DHT-11, the DHT library by Adafruit is used. Go here to download the library. When the letter “t” is received, the temperature, humidity, and heat index will be transmitted back via Bluetooth.

circuit to connect DHT-11 with Arduino
circuit to connect DHT-11 with Arduino

The code used to read data from the DHT sensor, process it and send it via Bluetooth:

#include "DHT.h"
#define DHTPIN 2 
#define DHTTYPE DHT11 
DHT dht(DHTPIN, DHTTYPE);
void setup() {
 Serial.begin(9600);
 dht.begin();}

void loop()
{ char c; 
if(Serial.available()) 
 { 
 c = Serial.read(); 
 if(c=='t')
 readSensor();
 }}
void readSensor() {
 float h = dht.readHumidity();
 float t = dht.readTemperature();
 if (isnan(h) || isnan(t)) {
 Serial.println("Failed to read from DHT sensor!");
 return;
 }
 float hic = dht.computeHeatIndex(t, h, false);
 Serial.print("Humidity: ");
 Serial.print(h);
 Serial.print(" %\t");
 Serial.print("Temperature: ");
 Serial.print(t);
 Serial.print(" *C ");
 Serial.print("Heat index: ");
 Serial.print(hic);
 Serial.print(" *C ");
}

Developing The Android App

The flow diagram of the Android app is illustrated below,

Flow diagram of the Android app
Flow diagram of the Android app

As this app will be using the onboard Bluetooth adapter, it will have to be mentioned in the Manifest.

uses-permission android:name="android.permission.BLUETOOTH"

Use the following code to test if Bluetooth adapter is present or not,

BluetoothAdapter bluetoothAdapter=BluetoothAdapter.getDefaultAdapter();
if (bluetoothAdapter == null) {
Toast.makeText(getApplicationContext(),"Device doesnt Support Bluetooth",Toast.LENGTH_SHORT).show();
}

The following part of the code deals with reading the data,

int byteCount = inputStream.available();
 if(byteCount > 0)
 {
 byte[] rawBytes = new byte[byteCount];
 inputStream.read(rawBytes);
 final String string=new String(rawBytes,"UTF-8");
 handler.post(new Runnable() {
 public void run()
 {
 textView.append(string);
 }
 });
 }

To send data, pass the String to the OutputStream.

outputStream.write(string.getBytes());

The complete source code of the Android application can be downloaded from here.

Testing

Power up the Arduino and turn on the Bluetooth from your mobile. Pair with the HC-05 module by providing the correct passcode – 0000 is the default one. Now, when “t” is sent to the Arduino, it replies with the Temperature, Humidity, and Heat Index.

the application screen
the application screen

Intel Introduces Loihi – A Self Learning Processor That Mimics Brain Functions

Intel has developed a first-of-its-kind self-learning neuromorphic chip – codenamed Loihi. It mimics the animal brain functions by learning to operate based on various modes of feedback from the environment. Unlike convolutional neural network (CNN) and other deep learning processors, Intel’s Loihi uses an asynchronous spiking model to mimic neuron and synapse behavior in a much closer analog to animal brain behavior.

loihi - Intel's self-learning chip
Loihi – Intel’s self-learning chip

Machine learning models based on CNN use large training sets to set up recognition of objects and events. This extremely energy-efficient chip, which uses the data to learn and make inferences, gets smarter over time and does not need to be trained in the traditional way. The Loihi chip includes digital circuits that mimic the brain’s basic mechanics, making machine learning faster and more efficient while requiring much lower computing power.

The chip offers highly flexible on-chip learning and combines training and inference on a single chip. This allows machines to be autonomous and to adapt in real time instead of waiting for the next update from the cloud. Compared to convolutional neural networks and deep learning neural networks, the Loihi test chip uses many fewer resources on the same task. Researchers have demonstrated learning at a rate that is a 1 million times improvement compared with other typical neural network devices.

The self-learning capabilities prototyped by this test chip have huge potential to improve automotive and industrial applications as well as personal robotics – any application that would benefit from the autonomous operation and continuous learning in an unstructured environment. For example, recognizing the movement of a car or bike for an autonomous vehicle. More importantly, it is up to 1,000 times more energy-efficient than general purpose computing.

Features

  • Fully asynchronous neuromorphic many core mesh.
  • Each neuron capable of communicating with thousands of other neurons.
  • Each neuromorphic core includes a learning engine that can be programmed to adapt network parameters during operation.
  • Fabrication on Intel’s 14 nm process technology.
  • A total of 130,000 neurons and 130 million synapses.
  • Development and testing of several algorithms with high algorithmic efficiency for problems including path planning, constraint satisfaction, sparse coding, dictionary learning, and dynamic pattern learning and adaptation.

Role Of Vision Processing With Artificial Neural Networks In Autonomous Driving

In next 10 years, the automotive industry will bring more change than we have seen in the last 50, due to technological advancement. One of the largest changes will be the move to autonomous vehicles, usually known as the self-driving car. Scientists from many universities are striving to implement vision processing with the artificial neural network to provide driver assistance in self-driving cars.

vision processing
Vision processing using convolutional artificial neural networks

Vision processing, as well as artificial neural networks, have been around for many years. Convolutional artificial neural networks (CNN) are sets of algorithms that extract meaningful information from sensor input. CNN’s are very computationally efficient at analyzing a scene. They are also able to identify objects as cars, people, animals, road signs, road junctions, road marking etc. enabling them to determine the relevant reality of the scene. As this system runs in real-time, the decision can be made as soon as the sensing part is complete.

One of the major steps in visual environment understanding for automotive applications is key points tracking and estimating ego-motion and environment structure subsequently from the trajectories of these key points. A propagation based tracking (PBT) method is popularly used to obtain the 2D trajectories from a sequence of images in a monocular camera setup.

The inputs from one or all of the sensors like LIDAR, RADAR, camera, IR, etc. are evaluated and decisions are taken accordingly. For example, if a car in the front suddenly brakes, the onboard computer would instantly verify the distance and calculate the speed with help of the existing sensors. Then it would apply the brakes faster than any human would be able to do. This method helps to prevent an accident with 90% efficiency.

The use of vision processing with CNN is rapidly increasing in automotive applications to enable camera-based autonomous driving. This technology sets a new driving standard. With this technology in our hand, fewer accidents, fewer fatalities, and less pollution are experienced. Vision processing in autonomous driving also enables efficient journeys, reduced crowding, car sharing, and packing cars in more tightly via vehicle to vehicle communication.

Researchers Developed Hybrid 3D Printing Method To Make Flexible Wearable Devices

Wearable electronic devices that intend to track and measure the body’s movements must be soft enough to flex and stretch to accommodate every body-movement. But, integrating rigid electronics on skin-like flexible materials has proven to be challenging. Clearly, Such components cannot stretch like soft materials can, and this mismatch frequently causes wearable devices to fail. Recently scientists solved this problem by developing a new method called hybrid 3D printing.

Making wearble devices using Hybrid 3D Printing method
Making wearable devices using Hybrid 3D Printing method

A collaboration between the Wyss Institute, Harvard’s John A. Paulson School of Engineering and Applied Sciences, and the Air Force Research Laboratory, has resulted in developing hybrid 3D printing method. It combines soft, electrically conductive inks, and matrix materials with rigid electronics into a uniformly stretchable device. Alex Valentine, a Staff Engineer at the Wyss Institute says,

With this technique, we can print the electronic sensor directly onto the material, digitally pick-and-place electronic components, and print the conductive interconnects that complete the electronic circuitry required to ‘read’ the sensor’s data signal in one fell swoop.

To make the circuits and the flexible layers, the researchers use thermoplastic polyurethane (TPU), both pure and with silver flakes. The method is quite easy to understand. As both the substrate and the electrodes contain TPU, they firmly adhere to one another while they are co-printed layer-by-layer. After the solvent evaporates completely, both of the inks harden, forming an integrated system that is both flexible and stretchable.

As the ink and substrate are 3D-printed, the scientists have complete control over where and how the conductive features are patterned. Thus they can design circuits to create soft electronic devices of nearly every size and shape. The hybrid 3D printing method enables development of flexible, durable wearable devices that move with the body.

A ring that is made using flexible conductingmaterial
A ring that is made using flexible conducting materials

Conductive materials exhibit changes in their electrical conductivity when stretched. Soft sensors, that detect movements, are made of those materials and are coupled with a programmable microcontroller to process those data. The microcontroller also transmits the data to communicate in a human-understandable way. As a proof-of-concept, the team created two devices – a wearable device that indicates how much the wearer’s arm is bending and a pressure sensor in the shape of a person’s left foot.

Watch the video to know about them,

Researchers Innovated Highly Effective Silicon Microchannel Thermal coolers For Processors

One of the limiting factors for the computing power of processors is the operating temperature. A research team led by Dr. Wolfram Steller, Dr. Hermann Oppermann, and Dr. Jessika Kleff from the Fraunhofer Institute for Reliability and Microintegration IZM, has developed a new as well as an efficient cooling method by integrating microchannels into the silicon interposer. For the first time, it is possible to cool down high-performance processors from the bottom as well.

The integration of microchannels into the silicon interposer
The integration of microchannels into the silicon interposer boosts cooling and processor performance

When processors get too hot to work properly, they reduce their clock speed and operating voltage. In order to protect the CPU and motherboard from getting fried, the processors either reduce their computing speed or even shut off completely. Until now, cooling elements and fans are used to avoid overheating the heat-sensitive components. The researchers found a way to cool processors from the top as well as from below using a liquid-based cooling system.

The research team reports that the innovation can achieve a significant increase in performance. The scientists have also integrated passive elements for voltage regulators, photonic ICs, and optical waveguides into the interposer. This enables highly effective cooling and therefore higher performance. For this purpose, microchannel structures with tightly sealed vias are installed in the silicon interposer, which is located between the processor and the printed circuit board.

Interposers are responsible for the electrical supply and cooling of the processor. Every 200 micrometers, interposers are equipped with electrical connections to ensure the processor’s power supply and data transmission. In order to be able to absorb heat and channel it away from the processor, the researchers at Fraunhofer IZM created microfluid channels that allow coolant to be circulated through vias.

The main challenge to the researchers was to integrate the small channels into the interposer and seal them very tightly in order to separate them from the electrical paths. The solution they came up with is interesting – the interposer is made of two silicon plates – horizontally extending cooling channels and vertically extending channels. They are combined in a complementary manner.

Dr. Hermann Oppermann, the group leader at Fraunhofer IZM, said,

Up to now, the cooling structures are not very close to the computer core itself, which means the coolers are mostly applied from above. The closer you get to the heat source, the better the temperature can be limited or the output increased. In high-performance computing, in particular, the data rates are continuously increasing. Therefore, it is important to have an effective cooling to ensure a higher clock rate.

Researchers Developed Highly Durable Washable And Stretchable Solar Cells

Scientists of Japanese research institute RIKEN and the University of Tokyo have successfully developed a product that allows solar cells to continue to provide solar power after being washed, stretched and compressed. Takao Someya of Riken Center for Emergent Matter Science, a designated national R&D Institute in Japan, led the research team.

Washable and stretchable solar cell
Washable and stretchable solar cell

The research results were published in the journal Nature Energy and illustrated a photovoltaic material that could be used to make washable outer garments and wearable devices. The researchers say that the innovated solar cells will be a power source to low-power devices and can also be worn concurrently. This innovation might solve one of the biggest challenges of the Internet of Things (IoT), the requirement of a reliable power source to keep all devices connected.

The newly invented solar cells could power wearable devices that include health monitors and sensors for analyzing the heartbeat and body temperature. This could make prevention and early detection of potential medical problems possible. Though the concept of wearable solar cells is not unique, the previous wearable solar cell solutions suffered from the lack of one vital property i.e. long-term stability in air and water, including resistance to deformation.

The recent stretchable solar cell innovation has successfully achieved all of the most important features and is creating the way for the top-notch quality of modern wearable technology. The material on which their new device is based on is called PNTZ4T – a highly efficient polymer solar cell capable of small photon energy loss. The scientists deposited the device onto a parylene film which was then placed onto an acrylic-based elastomer. The construction method has proved to be particularly very durable.

The device produced 7.86 milliwatts per square meter based on a sunlight simulation of 100 milliwatts per square meter before considering resistance and durability. It showed the least decrease in efficiency when soaked in the water and when stretched. The efficiency decreased by only 5.4 percent and 20 percent respectively. Kenjiro Fukuda of RIKEN Center for Emergent Matter Science said,

We were very gratified to find that our device has great environmental stability while simultaneously having a good efficiency and mechanical robustness. We very much hope that these washable, lightweight and stretchable organic photovoltaic will open a new avenue for use as a long-term power source system for wearable sensors and other devices.

PAC1934 – Microchip’s New Power-Monitoring IC Measures Power With 99% Accuracy

Microchip recently developed a precision power-and-energy-monitoring chip – PAC1934. The PAC1934 is a four channel power/energy monitor with current sensor amplifier and bus voltage monitors that feed high-resolution ADC. It works in conjunction with a Microchip software driver that is fully compatible with the Energy Estimation Engine (E3) built into the Windows 10 operating system. The whole setup provides 99 percent accuracy on all battery-powered Windows 10 devices.

PAC1934 - Software power monitoring IC
PAC1934 – Software power monitoring IC

The PAC1934 enables energy monitoring with a wide range of integration periods from 1 ms to up to 36 hours. Combining Microchip’s PAC1934 chip and Microsoft’s E3 service can enhance the measurement of battery usage by different applications up to 29 percent. The sophisticated digital circuitry of the IC performs power calculations and energy accumulation precisely.

The PAC1934 is able to measure voltage accurately as low as 0V and as high as 32V. This ability lets the chip precisely measure power usage from the Central Processing Unit (CPU) as well as from software running on devices connected through a USB Type-C connector. The chip has features that could make it an essential part of future software upgrades. No input filters are required for this chip as it uses real-time calibration to suppress offset and gain errors.

The PAC1934 measures bus voltage, sense resistor voltage, and accumulated proportional power. Then stores the data in 16-bit registers for retrieval by the system master or embedded controller. The data transfer between the chip and the host system is performed over SMBus or I2C. The sampling rate and energy integration period can also be controlled similarly. Another important feature is its highly configurable controls, such as Active channel selection and one-shot measurements.

Most important features are:

  • 100 mV full-scale voltage sense range, 16-bit resolution.
  • Bidirectional or unidirectional options.
  • Wide bus voltage measurement range 0V to 32V, 16-Bit Resolution.
  • 1% power measurement accuracy.
  • 48-bit power accumulator register for recording data.
  • 24-bit accumulator count.
  • User programmable sampling rates of 8, 64, 256, 1024 samples per second.
  • 36 hours of power data accumulation at 8 samples per second.
  • 2.7V to 5.5V supply operation.
  • Separate I/O pin for digital I/O 1.62-5.5V.
  • I2C fast mode plus (1Mp/S) and SMBus 3.0.

For more information on this IC, visit Microchip’s website here.

Researchers Develop Long Range Backscatter Sensors That Consume Almost No Power

Researchers at the University of Washington developed a new backscatter sensors that can operate over long ranges with very little power. The researchers demonstrated for the first time that the device runs on almost zero power and can transmit data across distances of up to 2.8 kilometers.

The long-range backscatter system developed by UW researchers
The long-range backscatter system developed by UW researchers

Backscatter communication works by emitting a radio signal and then monitoring the reflections of that signal from sensors. As the transmitter generates the signal, the sensors themselves require very little power. But this kind of system badly suffers from noise. Noise can be added anywhere – on the transmitter side, on the channel or on the sensor array. The key to solving this problem is a new type of signal modulation called chirp spread spectrum.

By using the chirp spread spectrum modulation technique, the team was able to transmit data up to 2.8 kilometers while the sensors themselves consumed only a few microwatts of power. Such extremely low power consumption lets them run by harvested ambient energy and very small printed batteries. The cost is surprisingly cheap too. The sensors would cost just 10 to 20 cents per unit if bulk purchased.

Today’s flexible electronics and other sensors need to operate with very low power typically can’t communicate with other devices more than a few feet or meters away. By contrast, the University of Washinton’s long-range backscatter system achieved pretty strong coverage throughout a 4800-square-foot house, an office area including 41 rooms, and a one-acre vegetable farm at extremely low power and low cost.

Shyam Gollakota, the lead faculty and associate professor in the Paul G. Allen School of Computer Science & Engineering, said,

Until now, devices that can communicate over long distances have consumed a lot of power. The tradeoff in a low-power device that consumes microwatts of power is that its communication range is short. Now we’ve shown that we can offer both, which will be pretty game-changing for a lot of different industries and applications.

These low-power sensors have endless potential applications. They can be used for everything from wearable health monitors to scientific data collection devices. Though there are no confirmed products yet, the team has created few prototypes in the form of flexible sensors worn on the skin, smart contact lenses, and more.

iEAT – A Powerful Keychain Detector To Detect Food Allergens

For kids and adults with food allergies, having meals from restaurants or hotels can sometimes be very risky. Even when ultimate care is taken, freshly prepared meals can accidentally become cross-contaminated with an offending food and trigger an allergic reaction. Every year many people end up in the emergency room due to food allergies. Researchers of the Harvard Medical School developed an affordable device called iEAT for detecting allergens, which can reduce the anxiety of the people prone to allergies.

iEAT - A Portable allergen-detection system
iEAT – A Portable allergen-detection system

Conventional methods to detect the hidden allergens require massive laboratory equipment. They are slow and also do not work on a low concentration of allergens. Ralph Weissleder, Hakho Lee, and their colleagues at the Harvard Medical School wanted to make a more practical, consumer-friendly alternative. They reported in the journal ACS Nano the development of a new portable allergen-detection system that features a keychain analyzer for detecting allergens in food anywhere, anytime.

The portable allergen-detection system called integrated exogenous antigen testing or iEAT is small enough to fit in your pocket and it costs $40 only. The iEAT consists of a handheld device to extract allergens from food and an electronic keychain reader for sensing allergens. Then, the result is wirelessly sent to a smartphone. The prototype is able to detect five allergens within 10 minutes, one each from wheat, peanuts, hazelnuts, milk, and egg whites, even if they are in very low concentration.

The main device uses a disposable sample collector which is inserted into the small-sized main unit. The device is so sensitive that the scientists were able to detect gluten in foods advertised as being “gluten-free”. For example, the device detected gluten in salad and an egg protein in beer. Although the prototype was primarily designed to sense five allergens only, the researchers say the device could be expanded to test for many additional compounds, including other allergens and non-food contaminants such as pesticides.