Author Archives: Andi

DIY Google Glass with Raspberry Pi

If you thought Google Glass was something beyond your capabilities, well you can think again. Adafruit has a Do-It-Yourself design that can turn a pair of display glasses into the coveted Google glass type of form factor. Not only does it clip to the prescription glasses you are using, it can display any type of device that puts out Composite Video such as the Raspberry Pi or RBPi does.

With 3D printed parts you can download free, one pair of these wearable video glasses will cost you only $100. The display uses simple plug-n-play technology to connect to the RBPi. The project uses the NTSC/PAL Video Glasses (1:20) and uses only one-half. The glasses are full-color LCD micro-display presenting a virtual large screen of 52” at 2m distance. With a resolution of 320×240, and a color depth of 24 bits, it has an in-built LiPoly battery rated at 800mAH, which lasts for 4-5 hours. You will also need miniature wireless USB keyboard with touchpad and of course, an RBPi.

Other parts that you will need for this project are a 3D printer to print out the parts, flat pliers, 30AWG Wire Wrap, a pack of heat shrink tubing, a screwdriver set and a composite video cable.

You start with disassembling the Video Glasses. First, remove the nose guard piece. For this, you may have to remove tiny screws – use a small screwdriver. Then, carefully pop the shaded lenses off. There will be more tiny screws behind the lens, remove them and the frame should come off easily. Now, gently pry open the enclosure and use a flat-head screwdriver to separate the two halves. Remove the PCB from its enclosure – use a pair of flat pliers. Also, remove the two video display screens from the enclosure. Holding the eye covers to the magnifying lenses, unscrew the two eyepieces. Now carefully detach one of the displays from the PCB and store away as a backup unit.

You will now have one of the video display units along with the kopin video processing circuit. The power circuit with its USB port and the two audio input jacks should also be present. With disassembly over, it is time to begin the assembly of the project.

Begin by unsoldering the four connections from the power circuit, as you will need to increase the lengths of the wires. Use about 140 mm or 5.6 inches of 30AWG wire to extend the length of the wires. You may need to tin the ends of each wire before soldering them together. Use heat shrink tubing to secure the connections. Disconnect all components before you put them into the enclosure.

3D print the eight pieces design to make the snap-fit enclosure. This will house the components extracted from the Video Glasses. The plastic eyepiece with the magnifying glass goes on top of the eye part. You can reuse the same screws to secure the eyepiece into the eye part. Positioning the eyepiece into the cap part, thread the cable connections through the opening on the side. Similarly, thread the wires through the elbow part and snap it in place. Assemble the rest of the parts following the guide here.

What are wireless power coils?

More than 120 years ago, a genius by the name of Nicholas Tesla conducted some experiments that laid down the technology of distributing electricity without wires. Today, we are using Tesla’s technology to charge our mobile phones. More than 50 million mobile phones remain alive through inductive charging. We use induction stovetops in our kitchens. The technique of wireless transfer of power is certainly proliferating.

A large part of the world population is completely dependent on smartphones and tablets. Personal encounters have given way to texting, emails and video chats. Spare times involve playing games on mobiles or watching videos. However busy people may be, there is always some time to browse the social networks and post in them. In fact, this gadget takes up most of the time we stay awake. With so much drain of energy, it is no surprise that mobile batteries do not last through the day.

Now, thanks to wireless power coils integrated into bedroom dressers or restaurant tables, people can charge their smartphones and other gadgets by simply placing them on the table. Device manufacturers adopt one of three major standards for Wireless Energy Transmission – WPC, A4WP and PMA.

The basis of Wireless Energy Transmission lies in Faraday’s Law of Induction. According to this law, a current flowing through a primary coil generates magnetic flux. If a secondary coil is present, the magnetic flux from the primary coil induces a voltage in the secondary coil. During wireless power transfer, the quality of the coils is of prime importance in determining the coupling and efficiency of the process.

The quality of a coil depends on its internal resistance and its reactance. Various factors affect both the parameters. For example, with a ferrite pot core, the coil can tightly bundle its magnetic field, reducing outward radiation while increasing the coil distance. Mounting space required is also smaller, since the coil is compact and round. Since the ratio of the area between transmitter and receiver coils affects the efficiency of energy transmission significantly, smaller receiver coils result in small transmitter coils as well.

Manufacturers reduce the internal resistance of their coils by using materials of very high purity. However, wireless energy transfer calls for the use of very high frequencies, for example, in the MHz range. At such high frequencies, the nature of current flow through the wire changes dramatically. High frequency current flows mostly along the outer periphery of the wire, with very little current flowing through the central core. As a result, the resistance of the wire increases tremendously as the frequency of the current passing through it goes up. This is called Skin Effect.

To reduce the resistance of a single wire carrying high frequency current because of Skin Effect, manufacturers replace it with a bundle of thinner wires insulated from each other. This type of wire is called Litz wire. Since the wires are thin and insulated from each other, the high frequency current is forced to travel equally through all of them. The overall resistance is therefore much lower.

Are Biometrics Related To The Internet Of Things?

With the Internet of Things or IoT, users and developers can easily augment its functionality, since the IoT is designed to be extensible. Therefore, it is not a far-fetched expectation that the IoT is going to be all over the place and users will get all types of data from it. According to a recent study by the Biometrics Research Group, biometric sensors are being projected as the next big step in providing the necessary security for accessing that data. That is good news for the biometrics industry – by the year 2018, IoT users alone will need nearly 500 million biometric sensors.

As against the normal practice of identification via a username and a password (which can easily be stolen), a biometric sensor identifies a person using unique physiological or behavioral traits, such as his or her fingerprints or his voice. Not only does this save time, the identification method is inherently more secure, making it more valuable. There is nothing like a password or a key to be misplaced, lost or forgotten. The best example of a biometric sensor in use is on Apple devices, with their Touch ID sensor for unlocking the device. In general, such sensors are typically used in security applications and in high-end access controls.

However, the consumer world is slowly making increasing use of biometric sensors, especially after the Fast Identity Online Alliance lent their support for these devices. The Alliance is a conglomeration of some of the biggest names in the technical and financial industry, and their aim is to create a roadmap for using different types of biometric sensors, policies and systems. Most of the use will be similar to the traditional systems, but the sensors will be linked to the Internet.

The Alliance is promoting the use of biometric sensors because of the real security benefits that consumers will get when they use them; the foremost benefit being the inability of losing your access capability. Although you could lose your key, forget your password or misplace your codes, there is only a very slim chance that you will lose your biometric access capability. And, the method is fast and convenient; you will never be locked out of your home or office.

The biometrics method of identification is also more secure than other methods. Even though attackers could cut off the thumb to use its fingerprint, it may not be of much use to them as biometrics can differentiate between living tissue and dead ones. In the same way, it is impossible to completely duplicate the retina pattern of the user’s eye or mimic the voice to fool the biometrics sensor.

With the IoT focus being strong on biometric sensors, the quality and reliability of the sensors is steadily improving. As consumers become increasingly more educated, affiliated technologies are becoming more popular, and that includes wearable devices with biometric sensors. As the popularity grows, so does the response speed of these biometric sensors. Coupled with falling prices, expect the use of biometrics sensors to go up in more and more devices.

How Are Brilliant Machines Created?

The IoT or the Internet of Things has one more feather in its cap. It has now conquered the industrial machine. With GE spearheading the initiative, the new type of industrial machines is aptly named Brilliant Machines.

Although GE is pouring nearly $1.5 billion into the amalgamation of industrial internet and big data, their plan is rather simple. The industrial internet is actually the business version of the Internet of Things. Instead of people being interconnected, here machines talk to each other. GE plans to mix that connectivity with analytics and software so that the entire arrangement becomes very efficient.

GE has started their foray with a battery factory. Covering a work area of nearly 180,000 square feet, the factory is packed with more than 10,000 sensors. Whatever happens within the factory, the sensors keep a track. This includes, for instance, the type of powders that are used to create the ceramics for use in the batteries and the temperatures of the ovens baking these ceramics. They also monitor the air pressure, the time each battery spends inside a particular oven or in a part of the manufacturing line. With smartphones connected via Wi-Fi, employees are able to keep track of all what is going on.

How does all this help GE? Gathering all this data, GE was surprised to find the cause of failure of some of the parts within a battery. The parts failed when they were left in the oven for longer time. Armed with this revelation, GE is able to cut wastage by monitoring how long specific parts stay in the oven.

GE makes investments in several areas. They make gas and steam turbines where over 52 million man-hours per year translate into $7 billion worth of labor cost and all this goes to service over 55,000 turbines. GE manufactures commercial jet aircrafts that take up 205 million man-hours every year. In the world there are over 120,000 diesel electric rail engines made by GE alone that require over 50 million man-hours for annual maintenance – roughly equal to $3 billion in labor cost.

By incorporating sensors within these machines and monitoring them, GE intends to lessen the time and cost of maintaining the various machines they use for power, healthcare, aviation and rail industries. Engineers collect the machine data on their smartphones, run it through visualization software and analytics, making it easier to interpret. The best part is that no engineer has to be near a machine or even onsite to monitor the machines. They can be anywhere on the globe and yet be able to relay accurate instructions to those on the site. The amount of time and costs reduced with the wealth of information available and its analysis is really helping GE.

Brilliant Machines help GE in asset optimization and problem solving, data collection and insights, generating situational awareness and improved collaboration. For instance, for the year 2013, GE earned segmented profits such as $1.2 billion for transportation, $3.0 billion for healthcare, $4.3 billion for aviation, $2.2 billion for oil and gas, and nearly $5 billion for power and water – that is, a total profit of $15.7 billion.

What is LED EOS failure?

LEDs, being semiconductor components, are susceptible to failure if overstressed electrically. This is true regardless of the manufacturer and electrical overstress or EOS is the leading cause of failure of LEDs. In fact, LED components are subject to transient conditions that can cause EOS and subsequently result in a catastrophic failure.

Like all semiconductor components, LEDs too have their maximum specifications of voltage, current and power. An exposure beyond the maximum current or voltage levels can lead to EOS. Typically, a current or voltage transient, accompanying the EOS event, may cause generation of localized heat – leading to EOS failure. As with any semiconductor device, an LED also has only a limited ability to survive overstress, and this is its maximum withstanding power.

EOS must not be confused with electrostatic discharge or ESD. Electrostatic discharge is the result of a rapid transfer of static electric charge between a non-operating part and an object at a different electrical potential. ESD events typically range from pico- to nano-seconds, whereas EOS events are much slower, ranging from milli-seconds to seconds. Moreover, EOS can be only a single event, an ongoing periodic event or even a non-periodic event. Common causes of EOS are:

• A driver producing current spikes
• A driver constantly driving an LED over its maximum rated current
• A lightning strike or similar power surge from the AC mains power input
• A user hot-plugging an LED into an energized circuit

Depending on the duration and amplitude of the overstress conditions, LED failures due to EOS can vary from subtle to severe damage. For example, an LED with subtle damage may not emit light at low currents, but does so at higher current levels. On the other hand, a severely damaged LED may not emit light at all. Both may exhibit current leakage, an open circuit or a resistive short. The amount of time that it takes for an LED to be damaged by EOS, depends on the conditions of the EOS, operating conditions and the LED junction temperature.

LEDs may be classified into three types – mid-power, high-power and COB. Test laboratories typically use square-wave pulses of forward current for simulating EOS conditions in LEDs. This allows variation of all test parameters such as voltage, current, power and time. For example, pulse power levels of up to 1700W may be applied to LEDs in forward-bias mode, while the time duration may range from 0.1 to 70 milliseconds.

Most mid-power LEDs are typically enclosed in a plastic package and contain either one or multiple chips. The multiple chips may be internally connected in parallel or in series. The EOS robustness of the device depends on the internal structure. As a thumb rule, LEDs with higher light output tend to be more robust to EOS.

The EOS robustness of high-power single-chip LEDs depends on their architecture. LED device structure, such as the packaging contacts, current spreading techniques and attachment of the die, are major contributors to determining temperature rise and power dissipation and hence EOS robustness.

COB or chip-on-board LEDs are similar to high-power single-chip LEDs, with one major difference. There are bond wires connecting the top-side contacts to the chips and metal traces for current spreading, resulting in lower withstanding power as compared to other high-power LEDs.

Raspberry Pi Temperature Monitor and Alarm Project

Although five-day weeks are a boon to white- and blue-collar workers, some businesses need to be extra careful during the two days of the weekend. For example, commercial monitoring systems generally protect warehouses with large freezers and cooler rooms. However, between Friday evening and Monday morning when the food shelf remains closed, a unit may blow a fuse. Usually, this goes unmonitored with the result that food is found ruined by Monday. The inexpensive, tiny credit card sized single board computer, the Raspberry Pi or RBPi was found to be a suitable base for a temperature monitor and alarm for a walk-in display-case cooler and freezer.

The project objectives are very simple. A low cost temperature monitoring system is required that can send free text messages when the temperature within the freezer or fridge goes outside the acceptable range.

For this, the RBPi has to monitor the temperatures within the fridge unit and the freezer. For the fridge unit, the valid temperature given is 33F, while it is -10F for the freezer unit. However, since stocking personnel and customers open the doors frequently during the business hours, temperatures in the fridge rises to 60F. Therefore, a wider temperature range is to be allowed during business hours as compared with the temperature range during off hours.

To draw the attention of maintenance personnel, the RBPi has to provide an audible temperature range alarm, which makes a noise when the temperature goes beyond the range. Additionally, a switch button is necessary, as a snooze, to silence the noise when the problem is receiving attention. As personnel are expected to be away on weekends, the RBPi is required to send a text message to someone who would be able to either fix the problem or move the food to a safer location. To make the temperature visible to the staff, an LCD temperature display is used. The RBPi is required to project the current temperature on a wall mountable LCD mounted outside the fridge/freezer unit.

Parts needed for the project include the RBPi Model B, although Model A can also be used. However, since Model A has only one USB port, an additional USB hub will be necessary. For the operating system, you will need the 8GB SD card with the NOOBS installer image. The Adafruit RGB 16×2 LCD kit with Keypad is the most suitable, since it has five momentary push-button switches useful for navigation. For connecting to the internet, you may use the Wi-Pi Wireless Adapter. In case you are planning for an XBMC solution, you will also need an Ethernet cable, an HDMI cable and wireless keyboard/mousepad.

For the audible alarm, you will need 2×3.5mm stereo headphone plugs, a portable speaker and audio cable. To house the RBPi, a suitable case will also have to be used.

You can use 2x DS18B20 Digital temperature sensors for monitoring the two temperatures. Although the stand-alone IC components are just as good, prepackaged waterproof units are available; these will suit the project better. When you are ready with the parts, follow the instructions in this tutorial to set up the project and to calibrate it.

How do motion detectors work?

Whether it is really a cat or a cat burglar trying to sneak into your house at night, a motion detector is a more prudent device to have around, rather than trying your luck with a baseball bat. The trick is in knowing what type of motion detector to use at what point, since there are so many varieties of them and that could be confusing. It helps to know how some of the more common types of motion detectors work.

Typically, there are two types of motion detectors – passive type and active type. The differentiation depends on whether a detector is injecting energy into the environment for detecting a change. Active types inject energy into their immediate environment, whereas, passive types do not. Both devices are simple electronic components.

Active type motion detectors can use light, microwaves or sound for detecting movement. The most common type of active motion detector is a beam of light crossing the door with a photo sensor on the other end. As soon as a person breaks the beam of light, the photo sensor detects the change for light reaching it and either rings a bell or flashes a light.

Many places have automatic door openers. These can detect when someone passes near and opens the door in response. A device above the door sends out bursts of microwave radio energy at periodic intervals. A sensor waits for detecting reflected energy. When a person moves into the range of the microwave energy bursts, the amount of reflected energy changes or the time taken for the reflections to arrive changes and the box triggers an arrangement that opens the door.

Pyroelectric sensors or Passive Infrared detectors can sense the heat given off by a human. To make the sensor sensitive to the temperature of a human body, the sensor must be capable of sensing skin temperatures of around 93°F or 37°C. Such sensors are typically sensitive to the infrared energy wavelengths of the range 8-12micrometers, since the human body radiates wavelengths between 9 and 10 micrometers.

To prevent the sensors triggering false alarms for example, a sidewalk cooling off at night, a pyroelectric type motion detector detects only rapid changes in its field of view. That makes these sensors insensitive to a person standing still. However, the amount of infrared energy changes rapidly when a person is moving or walking by, enabling the sensor to detect it easily.

Since infrared energy is a form of light, a plastic lens can very easily bend or focus it. That is how these sensors have a wide field of view. Most detectors have one or sometimes two sensors within them looking for changes in infrared energy. However, infrared sensors installed within a room are not very capable of detecting snoopers or peeping toms trying to peek in through a window. That is because a motion detector sensitive to infrared energy is unable to detect it through glass windows.

If you have a four-legged friend in your home, you have to get sensors that are pet immune, to make sure the friend is not mistaken for an intruder.

Teaching Raspberry Pi to teach itself

For most of us, learning is a part of life. Beginning at birth, we learn how to understand emotions, walk and talk as the primary steps in learning. For machines, although learning appears to be high-tech, it is not an isolated incident. We see incidents of machine learning around us almost every day without knowing. For example, machine-learning algorithms accomplish automatic tagging of Facebook photos and spam filtering of emails. Most of machine learning is a step in the direction of achieving artificial intelligence. Recently, a lot of interest has been generated by a new area of machine learning known as deep learning.

So far, only big data centers had confined this knowledge of deep learning, as deep learning technology depends largely on huge data sets. Only the big data-mining firms such as Microsoft, Facebook and Google had access to such large amounts of data. Now, a new startup Jetpac is planning to let everyone access this technology. Any person with a computing device can use their app to access deep learning technology, as the video on their website shows (https://www.jetpac.com/deepbelief). However, you may find that this technology is not so perfect. Just as the human brain, machines too suffer from optical illusions – confusing sidewalks with crossword puzzles, flutes with spiral bound notebooks and trash bags as black swans – see it below.

Pete Warden has done a great job of porting deep learning technology to the immensely popular, credit card sized, inexpensive single board computer, the Raspberry Pi or RBPi. The factor that has helped this process is that RBPi has a GPU with roughly 20GFLOPS of computing power, according to the documentation released recently by Broadcom, the manufacturers. That enabled Pete to port his SDK of Deep Belief Image Recognition to the RBPi.

If you would like your RBPi to be able to recognize things it sees around itself, follow the instructions here. However, for running the algorithm on the RBPi, you must allocate at least 128MB of RAM to the GPU and reboot the RBPi so that the GPU can claim the memory freed-up in the process. When you first run the program deepbelief on your RBPi, it will spew out a long list of different types of objects.

Thanks to the documentation about the RBPi GPU made public by Broadcom, Pete was able to write custom assembler programs for the 12 parallel ‘QPU’ processors that lurk within the embedded GPU. Additionally, the GPU makes heavy use of mathematics, which allows the algorithm process a frame in around three seconds. The technical specs of the graphics processor were released only a few months back, which has led to a surge of community effort to turn that into useable sets of examples and compilers.

Pete had to patch one of the existing assemblers heavily so that it could support more instructions. He had to create a set of helper macros so that programming the DMA controller was easier. Once these algorithms were tuned to the GPU’s internal method of working, Pete released them as open source.

Are drones invading your privacy?

Unmanned drones have proved to be a stealthy asset in the war on terror, making strikes on targets and collecting data on enemy movements. However, these small, nimble and nearly silent fliers can also be used to keep tabs on law-abiding citizens from nearby skies. This domestic use of drones is raising concerns about privacy violations including potentially violating the Fourth Amendment. Now APlus Mobile is planning to build a Linux-based Personal Drone Detection System. These will detect any nearby drone using a method known as Mesh Grid Triangulation.

The R&D division of APlus Mobile, the DDC or Domestic Drones Countermeasures, is planning to launch a device that will detect and track a drone aircraft that approaches within 50 feet. DDC has launched a Kickstarter project for building the Linux-based Personal Drone Detection System. They plan to make it available in November 2014, at $499 for the alpha test model, and in April 2015, at $699 for the beta test model.

DDC has a drone detection algorithm for which a patent is pending. The Personal Drone Detection System relies on this algorithm to work its magic. APlus Mobile will be using a MotherBone PiOne board-level Linux subsystem motherboard for building the device. The motherboard is an open spec PiOne type, which means it can fit either a BeagleBone Black or a Raspberry Pi single board computer.

The MotherBone PiOne is actually a part of the Primary Command and Control Module unit. This unit works in conjunction with two nodes of detecting sensors and establishes a mesh grid network. In turn, the network can triangulate the location of mobile transmitters. If you deploy more control modules and nodes, the network can cover a wider area.

The wireless mesh network and target triangulation work together. You can set up the nodes as far as 200 feet apart. Although the mesh network uses Wi-Fi to communicate, it is kept isolated from the user unlike the control module, which communicates with the user over Wi-Fi.

To detect the wirelessly enabled, mobile devices or drones, the sensor nodes use a frequency that ranges between 1 MHz and 6.8GHz. While detecting all known telemetry transmission frequencies, the system tries to determine if the mobile transmitter is actually a drone. All drones must transmit some telemetry data that allows it to navigate. Therefore, even if the drone is only storing recorded media and not transmitting it, it can be detected.

The biggest challenge for the drone detection algorithm will be in distinguishing between a jogger passing by with a cell phone and an actual drone. According to Aplus, the software does reduce false triggering. The system is designed to detect and trigger an alarm only if a drone is loitering nearby. Therefore, a jogger would have to stop for a while in front of the house for the device possibly to trigger a false alarm.

Once the device detects a drone hovering nearby, it sounds an alarm and simultaneously, sends a message on your mobile device. That should make you draw your infrared-resistant blinds and call for the police, unless the drone belongs to the police.

A Car Computer with the Raspberry Pi

There are many reasons one would want to make a car computer. Although one of the reasons might be the savings on the expenses of buying a branded one, the most plausible reason would be the thrill of making your own. What could be more exhilarating than to use the most inexpensive, credit card sized, single board computer, the Raspberry Pi or RBPi and turning it into a sophisticated car computer, ready to compete with the most expensive ones in the market.

That is exactly what Derek Knaggs did. He wanted a car computer and searched for one on the Internet – only to be put off by the large costs involved. As an RBPi enthusiast, he reasoned that his tiny RBPi had all the ingredients required to build one – flexible video and audio outputs HDMI and Composite RCA for video, HDMI and 3.5 mm audio jack for audio). Additionally, it has the complete flexibility of switching to any operating system simply by changing the SD card.

Derek made a list of the items he would need for his car computer – RBPi model B, a car DVD player, TFT monitors (7-inch models used, one for the front and one/two for the back seats), composite video cables, audio cables suitable for 3.5mm jacks), Wireless N USB dongle, Wireless mini keyboard and a micro-USB car charger.

Derek’s car already had a radio installed and he connected the audio output of the RBPi to the auxiliary port of the radio. That allowed the audio to be played via the car speakers, so he had stereo audio playing loud and clear. He placed the RBPi in the center console, so that he could route all the cables under the console, giving the whole arrangement a neat and clean look, without any cables hanging around.

For playing video on the RBPi, Derek used XBMC, which comes with the Raspbmc operating system. Inputs to the RBPi were controlled by the wireless keyboard, which also has a built-in mouse touchpad. The keyboard has an on-off switch, useful for saving its batteries. The Wi-Fi dongle gave Derek the freedom to connect to any wireless network. Of course, another option is to connect it to the mobile phone, provided it has the option to set up a portable Wi-Fi hotspot.

One of the TFT monitors connects to the RBPi, and although Derek chose to position it on the central console, you might want it behind on the headrest of one of the front seats. Since Derek already had a car DVD player fitted in, there was another TFT monitor available. If the TFT monitors have HDMI inputs, you may want to connect them via HDMI cables. TFT monitors typically come with RCA composite video inputs, so that should not be a problem, as RBPi has composite video outputs along with HDMI. However, as soon as you use one of the video outputs on the RBPi, the other switches off, so it is not possible to use two monitors at a time from the two types of video outputs on the RBPi.