Monthly Archives: June 2014

No more mobile phone batteries?

Now the time has come when you can do away with the battery of your mobile phone. A new material promises to transform the entire device of your phone into a super-battery, so you do not need batteries any longer.

Researchers have managed to combine the best features of batteries and super-capacitors into one single hybrid material. When made into a case suitable for the device, it can replace the battery. Although the energy density of the material does not yet stand up to that of a lithium-ion battery, it makes up for the lower density by the case being made up of a much larger volume. Additionally, the space that the battery normally occupies could now be taken up by the case.

Researchers call these hybrid capacitors. Actually, these batteries behave just like capacitors. They can maintain the ultra-long cycling lifetimes just as super capacitors do, but also store and deliver about as much energy as the current lithium-ion batteries can. Now they are trying to build this super-capacitor material into the structure of different types of constructions materials, such as sidings, drywalls of homes, chassis of airplanes and of course, cases of mobile phones.

One of the advantages in developing such energy storage materials that integrate into homes is the increase in the economic value of solar cells. These can be placed on the roof and they enable a distributed energy electric grid system.

Apple, in an independent research – for which they have filed a patent – have developed a photovoltaic touchscreen that harvests ambient light for keeping a mobile device with a super-capacitor case charged without a power cord.

Irrespective of the application, the purpose is to allow structural materials to store energy while retaining the same load-bearing durability. The structural materials thereby harbor inside them systems for storing energy and in many cases, their lifetime exceeds that of the objects for which they are acting as the building materials.

The major advantage here is that an extra battery compartment is no longer required. Either the device volume can be reduced by that extent or the structural material can double up for the redundant battery. Although these super-capacitors store about ten-percent less energy compared to lithium-ion batteries, they can make up for it in the volume where they are a part of the structure. Additionally, with an operating life more than a thousand times that of a battery, these super-capacitor-batteries are ideally suitable for mobile devices, homes, aircraft, automobiles, and more.

That makes eminent sense. What matters more is the total energy the product offers. With 10-percent less storage capacity, but distributed over a thousand discharge cycles, it means the material is capable of supplying 100-times more energy over the lifetime of the system. When such materials are used for building a home or the chassis of a car, it would be a nuisance if they required to be replaced every few years because they expired.

In the prototype, the super-battery had electrodes made of silicon wafers. One side of the wafers was covered with Nano scale pores and then with an ultra-thin layer of carbon. Between the two layers, is a polymer film holding charged ions much like an electrolyte in a battery. The whole structure is then solidified.

The Raspberry Pi-Fi bundle

The mighty single board computer, the credit card sized Raspberry Pi or RBPi, as it is fondly called, is making waves for all the good reasons. Developed by the Raspberry Pi foundation as a low-cost, hands-on for children learning about the inner workings of a computer, this tiny SBC has caught the imagination of hobbyists all over the world. As a result, people have developed innumerable projects based on the RBPi, and the flood shows no signs of abating.

For those still not initiated in the RBPi bandwagon, it is best to buy the SBC as a bundle. The Pi-Fi bundle will include the RBPi, a preloaded 8GB SD card, a Wi-Fi dongle along with an instruction manual “Getting Started with Raspberry Pi.” Add an appropriate power supply, a USB keyboard, a mouse and a display and viola – you have a fully functional Linux computer, fully Wi-Fi enabled, capable of playing games, writing programs, streaming media and web browsing. The USB keyboard and mouse is not a strict requirement. You may also use a wireless keyboard and mouse with their USB receiver.

Other sundry things you may need are an HDMI cable and a USB A to micro cable. Make sure the power supply is capable of supplying 5V at 1.0A on its USB port, and you are good to go.

To start, plug in your keyboard, mouse and monitor to the RBPi. Next insert the SD card and plug in the power cable between the RBPi and the power supply. Hook up the power supply to the mains and switch it on. On the monitor screen, the NOOBs (New Out Of Box) interface from your SD card will prompt you with a choice of the operating system you would like to install. If you dislike the OS you just installed, shut down, switch off, and reboot but hold down the shift key while the RBPi reboots. You will be returned to the NOOBs interface to select a new OS.

The RBPi consists of a System on Chip, a Broadcom BCM2835 that has a CPU, a 700MHz ARM 1176jZF-S and a GPU, a Broadcom VideoCore IV that supports MPEG-2, OpenGL, h.264/MPEG-4 AVC and 1080P. For memory, the SBC has 512MB of RAM, and an onboard storage of MMC/SD/SDIO card slot, for which a minimum size of 4GB is recommended. The board consumes about 700mA or 3.5W of power at 5VDC via the Micro USB or the GPIO header.

The RBPi is capable of outputting video as composite RCA or HDMI, audio via 3.5mm jack or HDMI. It has two USB-2.0 ports and a Micro USB port, exclusively for power. An onboard Ethernet network is available – 10/100 RJ-45. There is support for low-level peripherals such as SPI bus (along with two chip selects at +3V3 and +5V), I2C bus, UART and 8x GPIO or General Purpose Interface Bus.

If you are not too keen on an Ethernet cord dangling from your RBPi, simply plug in the wireless USB adapter to get 802.11b/g/n networks. In case power flakiness is observed, go for a powered USB hub to plug in the adapter. Wi-Fi requires substantial amounts of power.

Redefining computer vision

Google’s Tango prototype is a handset that can map 3D spaces simply with a walkthrough. That is possible because at its heart is the Movidius Myriad 1 vision processing unit or the VPU. According to Movidius, this VPU (not to be confused with video processing unit), is about ten times faster and has very little resemblance to GPUs or graphics processing units with which we are all familiar.

The VPU actually sits between the camera and the application processor in contrast to the GPU, which resides between the application processor and the display. However, that is only the beginning of their differences, since, as defined by Movidius, the VPU is an essential new component that will bring about astonishing changes to visual awareness in a camera.

The CEO of Movidius, Remi El-Quazzone, believes that all cameras, specifically the mobile ones are currently passing through a revolution and he calls this computational imaging, bringing in new functionality. He further explains that Movidius is developing visual processing units with functions similar to that of the visual cortex of the brain. The aim is to let the devices have the same kind of awareness and realism that the eye-brain combination has in the human body.

If you look closely at the graphical processing units, most are mere bit-bangers. These are vector processors performing identical operations on each pixel on the screen at extraordinarily high speeds. On the other hand, the VPU first interprets the data coming from the camera – very similar to what the eye and visual cortex do – before sending it to the applications processor. Therefore, instead of raw pixels, the application processor gets to work on high-level metadata, identifying where an object begins and where it ends, which ones are in front of the others, what kind of object each is, where its shadow is, the trajectory it is following, and other similar dozens of smart information. In fact, not only does it make the work of the applications processor markedly easier, it also makes possible Nuevo applications that no-one could have thought of earlier.

According to Remi, the Movidius methodology is to convert all the photons captured by the camera into metadata that expresses an understanding of the scene. Depending on the application, this metadata could then be used in a number of different ways. However, initially, they are looking into providing total visual awareness of the most relevant details in the scene.

Others have already explored the algorithms required by Movidius to perform such types of analyzes. They find that this requires supercomputers consuming megawatts to do the same. However, Movidius boldly claims that it is possible to equal or even exceed the visual awareness of such applications, consuming only few watts of power, and sometimes only a fraction of a watt.

Movidius claims a novel micro-architecture of cores entirely optimized for computational imaging. This involves structuring the delays between stages and an extremely innovative fabric of memory that allows maximizing the data localization. Since this drastically reduces the need for external memory accesses, it also reduces power requirements substantially.

Managing wearable smart devices

Unless you are confined to an ICU without a choice, no one likes to have a bunch of wires and cables trailing from their body to a machine. What people rather prefer is a user-friendly aiding system capable of remotely monitoring the health. Whether you are in a gymnasium or in an outdoor environment, practicing some sport or doing single exercises, remote monitoring of health parameters is a safe and efficient routine to practice. This is also true for monitoring the health of the elderly and people suffering from chronic diseases. IoT or the Internet of Things is able to bring effective solutions in this regard to improve a person’s level of fitness and health.

Wireless sensor networks or WSNs are very effective for building the IoT paradigm. This is the leading technology to acquire and manage data. For improving the user experience in the IoT, it should also be possible to connect to a WSN some other smart elements such as tablets, watches and smartphones. In fact, these could trigger the use of technology in this field. With smart devices now coming in wearable forms, it is easy to break down the first barrier for the technology-access – allowing the user simply to start wearing the technology as a daily-life garment.

Any WSN node has a differential value. Independent of the network management, data may be sensed with any external sensor connected to the WSN. For example, appropriate external sensors connected to the node can send feedback about the breathing rate, heart rate, blood pressure, etc., should the application require biometric or human physiological parameters.

Bluetooth, a wireless communication protocol, could be considered as an easy and fast solution. However, that scenario presents a new challenge, as there is no standardization in these types of sensors despite different type of devices or platforms being in existence. Therefore, it may be desirable to abstract the protocols and hardware features from high-level layers – an intermediate level of middleware can do this easily.

For integrating several wearable devices in the Internet of Things, a dual-protocol WSN/Bluetooth node is of immense help. In reality, two of these nodes are used. One connects to the wearable health-data monitoring device, while the other connects to the smartphone or the smartwatch. In this way, all data between the wearable device and the WSN node is managed in the same way as is done with information from other WSN nodes. As long as a new wearable device is Bluetooth compliant, its services can be discovered and used as well.

To model the services provided by the WSN, one can develop ontology, which again can be included within the service-oriented semantic middleware. This will enable the user to compose new services based on the existing single services. These semantically annotated services will be able to widen the platform for future applications.

It is also possible to integrate the enterprise service bus or ESB within WSN for IoT-based applications. That enables third party applications to be used for services of wearable devices to be made available with the ESB and published by the WSN nodes. These may include body temperature and heart rate monitors.

How do rotary encoders work?

When tracking the turning of shafts, it is usually necessary to generate digital position and motion information. The most popular way of doing this is by using rotary encoders. They may be incremental or absolute, optical or magnetic, but they are used extensively in industrial and commercial designs in myriad applications. You will find rotary encoders being used on motors paired with automated machinery and drivers for nearly everything from robotics, position control and conveyor speed monitoring on automated industrial machines, elevators and consumer electronics.

Incremental encoders, mostly used for industrial applications, output the shaft’s relative position compared to a reference. In contrast, absolute encoders provide a different binary output for each position that defines a shaft’s position absolutely. Where incremental encoders define resolution as counts per turn, absolute single turn encoders define it as positions per turn, and express it as a multi-bit word. There are multi-turn encoders that track over multiple 360-degree turns and they specify resolution as positions per input-shaft turn along with the number of internal gear ratio turns.

Rotary optical encoders are the most widespread designs used. They typically consist of an LED light source, light detector, a code disk and a signal processor. Although the precision of the mechanical pattern on the code disk defines the measurement precision, there are other factors as well. For example, a quadrature encoder has several opaque regions that produce four distinct reference points. Two of these points correspond to the leading and trailing edges of the region itself. Another two additional points correspond to the leading and trailing edges of a second detector. Apart from providing higher resolution – four times of the code disc – it also indicates direction of turn depending on which detector responds first.

Incremental encoders are named after their outputs, which consist of two square waves, each corresponding to one increment of rotation. A convex lens focuses the light rays from the LED into a parallel beam. This passes through grid diaphragm, whose sole purpose is to produce a second beam of light 90-degrees out of phase to the original. Light from both channel A & B pass through a rotating disc onto the photodiode or photovoltaic array. The rotating disc creates a light & dark pattern as the clear and opaque segments interrupt the beam.

The absolute encoder has a nearly similar structure, except for multiple detectors and multiple unique tracks on the rotating disc. This produces a Gray Code output, which is a binary numeral system where the successive values differ by one bit. One advantage is this information is available even if the encoder has been temporarily shut down.

Although several methods are used to boost the resolution of direct-read encoders, the electric interpolation method is the most widely used. A voltage divider circuit subdivides the raw analog signal into the number of interpolation steps desired. The interpolation is actually a function integrated into the encoder logic and is transparent to the designer. This method allows for boosting the direct-read encoder resolution by about twenty times.

High density card edge connectors

Sullins Connector Solutions, Inc., a San Marcos company from CA, has recently been including the FMBx series in their offerings. That has expanded their range of high-density 0.050-inch contact center card edge connectors. The company makes multiple versions of these connectors for various users. The new versions that are now available feature ultra-thin low profile and include high temperature devices that accommodate thicknesses of 0.093, 0.062 and 0.031 inches. At the same time, these versions support operating temperatures in the range of -65°C to +200°C. The low profile, ultra-thin interconnection are unique as their profile is only 0.488 inches.

The company is also offering 1.00mm versions that function within the same operating temperature range and these are ideally suited for ODMS and OEMs. The company, with its efficiency in manufacturing, is offering flexibility in design offering the customer maximum benefit. They make the connectors with an array of terminations, which includes surface mounting types, through-hole types, right angle or card extender types and types with staggered dip solder options. With the new product release, along with flexibility in design, the company is able to meet the diverse needs of the customer.

Sullins provide important features for their high-density card edge connectors along with several variations. For example, the 0.050-inch connectors, with operating temperatures of 200°C, are available with a low profile of 0.488 inches. In cases where there is a higher demand for thermal applications, profiles of 0.039 inch and 0.050 inch with operating temperatures of 125°C and 150°C are being offered. Based on the type of mating board and material selected, the reliability can be as high as 500 to 5,000 cycles. Options are available for card guides and molded key slots. Similarly, users have a choice in selecting the type of material, mounting styles and type of termination. In the market, the 0.050-inch connector is the only one rated at 3A.

Applications for these connectors are extremely diverse and widespread. The major areas among them are Radio Communications and Aircraft electronic Controls. They are also used in peripherals and computing equipment. You can see these connectors in Household Appliances, Consumer Electronics, Telecommunications, Burn in Ovens, Test Equipment, Casino Gaming Devices, Process Control Equipment, Industry Machinery, Medical Devices, and so on in a multitude of devices. The high-density card edge connectors cater to all these applications because of their flexibility in design combined with the company’s manufacturing efficiencies.

Sullins Connector Solutions started their operations in 1971 modestly. However, they are now positioned as a leader developing extremely reliable cutting-edge connectors. The Sullins now cater globally to very diverse applications. The company offers free samples on fast mode with only five days lead-time for shipping the customer’s confirmed order. Customers always have the backing of their technical support with connector experts to help on any specific project. The company is now offering 100% UL, CUL, and RoHS certified edge cards. The market is definitely going to benefit from the Sullins’ high-density edge card connectors with multiple options.

Cassandra on a Raspberry Pi

The Cassandra database typically runs on large clusters of computer systems as it is designed to hold massive amounts of data. Now, a lecturer from the Dundee University is running it on the tiny, credit card sized, single board computer – the ARM based Raspberry Pi or RBPi.

At the Cassandra Summit, 2013, Andy Cobley, a lecturer at the University of Dundee, Scotland, presented his process of running Cassandra on multiple RBPis, which work as multiple Ethernet connected computers for his students. The advantage – no server racks and no data-centers required.

With 512MB of memory and a 700MHz ARM processor booting off an SD card, the Linux running RBPi does not look like a suitable candidate for usefully running Cassandra – the big data oriented Java-based database. Facebook originally contributed Cassandra as an Apache project. Organizations such as CERN, Twitter, eBay and Netflix use it to process huge amounts of data. For this, they use powerful servers in multiple data centers. Cassandra stores data and spreads the load over several clusters of connected disks and RAM loaded servers and connecting these clusters over highly constrained links results in an internationally reliable and resilient database.

Andy Cobley wanted to make it possible to run Cassandra on multiple RBPis, so that his students could experience running a database on multiple computers connected via the Ethernet, without having to build data centers and server racks. For this, Andy had to accept some compromises.

Cassandra is designed so that it can write data to disk at high speeds. Typically, in the time a laptop completes 12,000 write operations, a single RBPi can manage only 200 writes to its SD card. Making it write to an external USB drive only slows it down further. Moreover, the Ethernet port of the RBPi shares the same bus as its external USB port and the SD card. Cassandra, being very network centric, sees drastic reductions in network performance when there is any improvement in disk performance. Therefore, the route data takes through a system affects its performance.

With four to eight RBPis powered from USB hubs and all attached to an Ethernet switch, Andy was able to run Cassandra. Each of the RBPis was running the Debian Linux variant Raspian. Although he was unable to run the current Oracle JDK with the above setup, he ran Cassandra over OpenJDK. Running Cassandra in this manner, although complicated, resulted in some bugs being fixed for Cassandra. For example, Andy had to make the startup script resilient to accepting no CPU cores in the system.

Cassandra uses compression for boosting performance. However, it was not possible for Andy to use the native default method – Google’s Snappy compressor. Instead, he had to settle for the Java-based Deflate compressor, which is slower and has a penalty in write performance. Further performance boost for Cassandra came from ensuring that the RBPi CPU has more memory as compared to its GPU.

Andy has scaled down the Cassandra platform for his students, without actually rewriting it, making it easier for them to examine how a combination of Linux and Java runs on an RBPi cluster.

The compute module for Raspberry Pi

If you thought that the tiny single board computer, the Raspberry Pi (RBPi), could get no smaller, well, you really need to think again. There is now a Compute Module, which is much smaller. It contains the processor of the RBPi and 4GB of memory. The size of this board is roughly equal to a DDR2 laptop memory stick. However, the Compute Module is not exactly a miniaturization of the RBPi.

The advantage in fitting the system onto a small connector-less standard circuit board allows users to attach their own choice of interfaces. They need not be tied down to the built-in ports and devices that are available on the conventional RBPi board. The Compute Module is used along with a Starter IO board, which contains the rest of the devices.

The combination of the Compute Module and the Starter IO board is aimed at business and industrial users. The idea is to free the core technology of the RBPi to become an integral part of several new and exciting products and devices. The software of the RBPi is now full-featured and stable. A heroic community of volunteers is always hard at work constantly improving and improvising on the software. The manufacturers feel that this is the right time to free the hardware of the RBPi and make it more open.

Looking at the different types of users putting the RBPi to good use, it is really amazing to witness the huge number of products the community is developing around the tiny credit card sized SBC. The creativeness, ingenuity and inventiveness of the users are simply stunning. People are using the RBPi as not only a standalone module, but also embedding the tiny SBC into commercial products and systems. The dual combination of the Compute Module and the Starter IO board will make it even more versatile for these users.

The Compute Module contains the guts of the RBPi – the BCM2835 controller along with 512MBs of RAM. It also has a 4GB eMMC Flash memory, as a replacement of the SD card on the RBPi. Although all this is integrated onto a DDR2 SODIMM standard connector of the size 67.6x30mm and looks very much like a laptop memory card, it is not pin compatible to the memory card. Therefore, do not make the mistake of plugging in the Compute Module into a standard memory slot; it will only end in disaster.

The flash memory on the module is connected directly to the processor, but the remaining interfaces of the processor are freely available on the pins of the connector. That means you now have the full flexibility of the BCM2835 SoC. Compared to the original RBPi, many more number of GPIOs and interfaces available to the user on the Compute Module. That makes interfacing the Compute Module into a customized system should now be relatively simpler.

Although the Compute Module is aimed primarily at users who will be designing their own PCB, others not willing to go that far may use the Starter IO board. Snap the Compute Module into its connector on the Starter IO board and you are good to go.