Internet of Things can grow Customer Lifetime Value   Leave a comment

Customer lifetime value (CLV) is an important metric as it captures the revenue potential of each customer relationship over their lifespan with a company. Higher CLVs lead to greater profits for the enterprise, and now, with the rise of potentially billions of cloud connected sensors and smart devices collectively known as the Internet of Things (IoT), there are more opportunities than ever before to grow both.

The IoT relies on sensors and machine-to-machine (M2M) communications to produce data on a variety of subjects. Translating that data into more rewarding customer experiences is one of the most significant opportunities that comes with the Internet of Things. Here are three ways any enterprise can mine IoT data to cultivate deeper customer connections and generate higher per-customer revenues.

1.Monetize IoT Data by Expanding Offerings:

One way to improve Customer lifetime value CLV is to use data created by IoT devices to give existing customers new ways to consume products and services — and more reasons to remain loyal. Adding IoT-driven services to an existing product catalog can help marketers meet fast-changing customer demands and keep competitors at bay.

For example, in the offline world, auto insurers like Progressive are accommodating their cost-conscious customers by offering them new pay-as-you-drive policies where rates are based on the miles actually driven. Mileage is tracked and sent to the insurance carrier through a small IoT-connected dashboard plug-in. Consumption-based policies such as these can lower premiums by as much as 50 percent – a powerful incentive for insurance customers to stay put.

Cable TV providers are especially adept at the repackaging game. It’s how they fend off subscriber churn. Earlier, they expanded beyond TV with triple play packages that added Internet and phone services to the mix. With the advent of IoT, they’ve now added another: smart-home monitoring. These systems combine motion sensors, cameras, smart locks and brainy thermostats that allow cable customers to remotely manage hearth and home from anywhere. Subscribers who sign up for these services view them as a convenience they can just add to their existing bill. That’s exactly the mindset companies want their customers to have if the objective is to increase CLV.

In the online realm, MyFitnessPal, the world’s top online health and nutrition membership community, is embracing IoT to make it even easier for its more than 80 million members to reach their goals. They can now add personal data from their favorite wearable IoT fitness gadgets like Fitbit and Jawbone to the other health information they track on MyFitnessPal. Providing an in-demand service like this pays off for the website, even though its CLV is difficult to pin down because the site is free to join and ad-supported. Earlier this year, sportswear maker Under Armour purchased MyFitnessPal for $475 million. Clearly, its goal is not only to monetize the site, but also to tie it into its own sales of IoT trackers, including computerized performance wear.

2. Improve your website experience to deepen engagement:

For any company that sells online, one of the most obvious means for growing CLV is to improve how visitors engage with the website. Data gleaned through the IoT can provide a clue. Several vendors offer sophisticated analytics that can help brands identify site issues that may be causing lost sales and missed connections. Some companies uses IoT advancements in M2M learning and powerful algorithms to assess the way visitors interact with websites. The solution tracks subtle variations in customer clicks, scrolls and mouse movements in real-time so designers/marketers can better understand both behavior and intention.

3. Get personal to boost customer satisfaction and loyalty:

Relying on the IoT to make a website more personal is only the beginning. The truth is, the technology serves up personalization opportunities in spades. An expanding universe of smart sensors and devices
generate continuous streams of personalized, real-time data on just about anything people want to monitor and manage — from heartbeats, footsteps and sleep cycles to inventory levels, shipments in transit and medical diagnostic equipment.

Consider online streaming TV pioneer Netflix. It’s made a science of personalization, due in part to its
reliance on intricate M2M processing. For example, each day, it tracks millions of viewing streams from its customers. From this data, it not only offers customer specific viewing recommendations based on predictive analytics, but also shows individual subscribers exactly what they’ve already watched and even where they paused a particular show, no matter what device they use when they return.
Personalized experiences like these are a key reason behind Netflix’s outlandish success.

Indeed, endless digital rivers of IoT data hold a veritable treasure trove of information brands can harness to transform customer satisfaction and increase CLV. That’s because most IoT products and services leave a digital trail that reveals details about the way customers use and interact with them. Consumption data provides an unprecedented view into customer behaviors, preferences and usage patterns. With these insights, it is possible to produce perfectly timed, spoton offers and incentives that
customers increasingly expect.


Health Services on Wearable Devices   Leave a comment

Healthcare systems around the world are facing a ‘perfect storm’, contending with rising costs, changing demographics and growing consumer expectations.  PA Consulting in the UK concluded that a vital component in helping to solve these problems could be the use of ultra-low-power wearable technology. Wearable technology, increasingly enabled by miniaturised ultra-low-power electronics, is said to be used by 8million people in the UK already, with many of those devices being healthcare related.

The benefits of wearable devices are threefold,  they can act as a ‘digital lifestyle coach’; provide unobtrusive monitoring of patient data; and drive efficiencies in the delivery of treatments.  People are voluntarily embracing consumer products ranging from heart rate and sleep monitors to pedometers. Unobtrusive sensors, when combined with the connectivity enabled by the Internet of Things, are making it possible to deliver on-going care, as well as allowing clinicians to collect long-term data and make more informed decisions as a result. The advent of wearable appliances and ubiquitous connectivity could provide the impetus needed to finally make such initiatives a reality.

A ‘wearable’ can be defined as a product that is worn by the user for an extended period of time and which enhances their experience as a result of the product being worn. But add connectivity and independent data processing capabilities, and you have a ‘smart’ wearable device. Bio-stats, for example, are vital signs that measure the human body’s basic functions and can be used to indicate an individual’s state of health. These can include body temperature, pulse/heart rate, respiratory rate and
blood pressure.

Traditional patient monitoring has usually required a trip to the doctor or hospital; wearable solutions, by contrast, can offer an efficient and inexpensive alternative enabling these stats to be measured in the home or at work. As a result lifestyle and behaviour modifications could be suggested and made in real time.

Semiconductor manufacturer Ams has developed a new optical heart rate sensor for use in wrist wearables. The device, the AS7000, has been designed to measure a person’s heart rate by shining light into blood vessels, using a technique known as photoplethysmography (PPG), which works by analysing scattered reflections. The device includes two green LEDs and a photosensing signal processing IC based around an ARM Cortex-M0, the module has been paired with an external accelerometer which allows internal algorithms to handle several potential causes of interference and

The main challenges for measuring PPG on a wrist-worn device are the impact of ambient light, cross talk and motor-generated artefacts.  But light from fluorescent and energy saving lamps carry frequency components that can cause AC errors. Analog Devices, which has developed the ADPD142 optical module, uses two structures to reject this type of interference. After the analogue signal conditioning, a 14bit,
successive approximation A/D converter digitises the signal, which is transmitted via an I2C interface to a microcontroller for final post processing. The device includes a synchronised transmit path that is integrated in parallel with the optical receiver. Its independent current sources can drive two separate LEDs with current levels programmable up to 250mA. The LED currents are pulsed, their lengths being in the microsecond range, so the average power dissipation is kept low.

Sensor technology and falling device costs means that wearable technology is becoming increasingly practical, whether as simple ‘single vital sign’ unit that can be attached to the body, such as the AS7000, or in more sophisticated full body sensor filled exoskeletons. The core architecture of a smart wearable has to be a combination of parts such as a microprocessor or microcontroller; some sort of micro-electromechanical sensors (MEMS); mechanical actuators; Bluetooth/cellular/Wi-Ficonnectivity to collect/process and synchronise data; imaging electronics, LEDs; computing resources; a battery pack and support electronics.


Multi User, Multi Input Multi Output   Leave a comment

MU-MIMO, which stands for Multi-User, Multi-Input Multi-Output, exists to solve a problem faced by its predecessor, Single-User MIMO (SU-MIMO). MIMO itself means that a router has multiple antennas, each capable of emitting one spatial stream of data. The issue with this is that most devices do not have that many antennas themselves, and are thus not capable of taking in the full data output of a router. Add the fact that SU-MIMO does not allow for the multiple antennas to serve different client devices at a time, and the result is wastage of the router’s full capacity, called the MIMO gap.

SU-MIMO and MU-MIMO operations


Instead of pushing all the data to one device that can’t make use of it all, MUMIMO means that the spatial streams are split between the other devices that are connected to the network.

MU-MIMO closes this gap by splitting its individual spatial streams to serve one device each, resulting in, theoretically, an equally high speed enjoyed by up to four devices per router or access point. With MUMIMO and devices supporting this technology, the multiple streams are spread out among the clients, meaning each gets its own stream of data.Another result of this is the router is capable of sending more data out at a time, closing the MIMO gap.



With MU-MIMO, devices are each taking one spatial stream of data, meaning there is less wait time caused by the turn-taking of multiple devices sharing all spatial streams.

Still, MU-MIMO has some drawbacks of its own, chief among which being adoption. So far, there are few client devices out there that support MU-MIMO, and you will need such devices to truly take advantage of this feature. And while still faster than using a router that does not support MU-MIMO, if a device that does not support MU-MIMO connects to a MU-MIMO access point, other connected, MU-MIMO
supported devices will experience a dip in speed. This is because the router will have to serve the legacy device with data the old-fashioned way – by pushing all four spatial streams of data to the device, despite
the device being incapable to make full use of it. Other devices will also have to take turns in getting data from the router, to accommodate the device that doesn’t support MU-MIMO.

Of course, all that is in theory. To make sense of all this, we ran a test ourselves with the aforementioned Linksys EA8500, an AC2600 router that supports MU-MIMO. Also with us are two Acer Aspire E14 notebooks, one of the earliest adopters of MU-MIMO among notebooks. We plugged in a USB flash drive containing 4GB worth of video files to the router, and first copied it from the drive to one of the notebooks. The process took two minutes and 14 seconds, with data transfer averaging at 31MB/s. We then repeated the test, this time with both notebooks. Transfer speeds took a dip here, going down to an average of 23MB/s, with the file transfer completed in three minutes. We would attribute the drop in speed to processing bottlenecks on the router’s end because of one key factor: in other, non-MU-MIMO routers, the ordinary observable pattern is to see the transfer speed of one system dip while the other climbs. This wasn’t the case here: the speeds of both transfers rise and fall independent of each other, sometimes climbing and falling together,perhaps due to interference and processing limitations of the router. Also, with two devices going at 23MB/s simultaneously, this means a higher output from the router, going at a total of 46MB/s, compared to 31MB/s when serving a single notebook.

To push things further, we connected a Lenovo IdeaPad Z470 with an 802.11ac adapter to the router, and made it copy the same set of files together with the two Aspire E14s. The two MU-MIMO notebooks suffered another dip in performance, pulling down the average transfer rate to 18MB/s and completing the process in four minutes and 14 seconds. The IdeaPad, however, remained crawling at 1MB/s transfer rate until the two Aspire E14s were done, before going back up to averaging at 10MB/s.

Wireless sensor networks in the Internet of Things   Leave a comment

As the market for the Internet of Things starts to take shape, the role of wireless sensor networks in enabling a range of new applications, has started to take centre stage, with demand growing for extremely low power solutions.

While sensor-based networks for monitoring and control are not new concepts, demand for wireless implementations – previously limited to just a few niche markets – is set to grow as companies look to bene8t from the combination of installation simplicity and low-cost.

Wireless systems need to consume as little power as possible and next generation networks are being developed where batteries require little maintenance over the application’s life time. As an alternative, there is also a focus on energy harvesting to provide the necessary power, removing the need for batteries completely.

Energy harvesting is becoming  more attractive because it doesn’t require continual recharging and does away with the need for communication or power wires. The challenge with its deployment comes when it needs to be located in more challenging environments and especially when power needs to be stored. If you have to incorporate temporary storage capabilities in a design, then the application will, as a necessity, become far more complicated – cost, as a result, then becomes a more important issue, especially if you are distributing hundreds or thousands of sensors.

Applications have different power requirements. A door lock, for example, may only have to report back every hour or when something happens. As a result the power requirements will be low. By comparison, some wearable devices, such as the Apple Watch, consume far too much power to deploy a harvesting solution. The challenge is being able to develop an MCU that is capable of driving an application but which comes with very low power consumption. When powering sensors is that energy harvesting may only be able to supply as little as 10μA ontinuously, especially if the energy source is a small solar panel.

By contrast, a microcontroller executing code will have power requirements hundreds or thousands times greater. As a result, application designs will need to be able to fully leverage various sleep modes and should be designed with a view to putting the application into sleep mode as much as is possible.

Most applications will come with a variety of preset operating modes, so the embedded microcontroller can, for example, be put into a ‘sleep’ or enter an extreme, low-power ‘standby’ mode in between different data samples. If the microcontroller collects sufficient data, it can then switch to a ‘fully on’ mode, where it is awake and running at maximum operating speed. This will require the microcontroller to receive some kind of wake-up event, which could be triggered by an external event or by internal processor activity.

From an ‘always on’ mode to a ‘sleep’ or ‘standby’ mode, where memory stays powered, or a ‘deep sleep’ mode, where the memory is powered down for maximum power savings, the choice of a microcontroller’s power modes can have a significant impact on the overall power requirements of an application.

The problem with energy harvesting solutions is the energy output might be too low to power up the MCU. Starting an MCU  will require a lot of current; more than the energy harvesting component can provide. As a result, you need to deploy a mechanism whereby the MCU will only start-up when sufficient energy has been stored, usually a capacitor to store the energy and a comparator capable of detecting the amount of power available.

Once the application has powered up, it can then return to a more suitable power mode. It means the application has greater stability.

Accurate timing is needed to ensure the wireless sensor transmits information during a predefined assigned time slot, which will enable multiple wireless sensor nodes to work together.

The overall power budget of the wireless system, the transmit power consumption, the receiver power consumption, the standby power consumption, and the start-up time are all important considerations and will determine how much current the unit will consume when transmitting and receiving data.

To minimise the overall power consumption, it is not enough to simply select the lowest-power mode on the microcontroller as the amount of work needed to complete each of the tasks will need to be taken into account and as the Internet of Things develops and the amount of data collated rises, how and when that data is processed will become more important. At the moment, batteries remain the dominant way in which power is stored and delivered. While there has been a lot of discussion around energy harvesting, it really hasn’t taken off.

When you develop a network, there will be a power budget for computation and for communication. Hopping from one node to another to get that data to a point where it can be processed can be described, in effect, as an energy tax that you are taking from that packet or payload. Minimising those hops could be one trade-off leading to more localised processing should those tasks be more power intensive.

In many low-power saving mode systems, the application’s battery life will often be affected by the current consumption of other components in the PCB and this needs to be considered. components in the PCB and this needs to be considered. Designers will also need to  determine which other circuits need to be powered in the low-power state of the application. Power requirements will have an impact on the roll out of the Internet of Things, but everything will depend on the application.

Cost and power among the challenges to rolling out of IoT applications, but note that, further down the road, security is another consideration. Consumers will start to worry when they begin to realise the devices they are using are less secure than they thought. When you connect to a network, there are some
expensive operations that need to be carried out and that will have an impact. Any security features will
need to be low power.

The future of your health is on the Internet   Leave a comment

You didn’t know that you could prevent chronic diseases like heart failure, obesity and stroke using the Internet. With tech and healthcare you can.

“Prevention is better than cure.” That’s why we’re encouraged to eat more vegetables than meats, exercise, more than sit, and sleep more than play videogames.

But do these things really help? How would we know for sure that we’re actually becoming healthier with the lifestyle changes we’re making, and not staying the same, or even getting worse?

Juliett Starrett is a CrossFit athlete and the co-founder of San Francisco CrossFit. After giving birth and receiving a blood transfusion, Starrett kept feeling fatigued and getting chronic headaches.

The doctors put her on antibiotics, and thought it was just temporary. But even though Starrett was both extremely health-conscious and fit, she didn’t get better. To help her get through the day, Starrett resorted to drinking eight cups of coffee a day.

Starrett started working with WellnessFX. WellnessFX is a webbased service that combines traditional blood tests with intuitive online data tracking and phone consultations with physicians. Using WellnessFX, Starrett discovered that her iron, vitamin B12 and D levels — indicators of physical energy — were extremely low.

Thanks to WellnessFX’s ability to track biomarkers over time, Starrett changed her lifestyle, diet and supplements to attack her deficiencies. Over the next few months, her energy levels improved significantly, and she could cut her coffee down to a cup a day.

Not only did she feel better, Starrett could actually measure her improvements, using WellnessFX’s regular blood tests and online data tracking, to quantify how her biomarkers changed over time.

Tracking your biomarkers over time isn’t just something for elite athletes — according to the Center for Disease Control and Prevention (CDC) in the United States, chronic diseases and conditions, such as heart disease, obesity and arthritis, are among the most common, and preventable of all health problems.

By monitoring your blood over time, you can track and stop markers like cholesterol, inflammation and blood sugar before they hit unhealthy levels.

Internet-connected health services aren’t just good for preventive care. In 2014, the University of California, San Francisco, began offering patients the use of a miniature wireless device called the CardioMEMS HF System implant.

The CardioMEMS is a battery-free device that’s smaller than a coin. It monitors the patient’s heart rates and artery pressures, and transmits them in real time to the hospital. Not only does it help doctors measure how patients are responding to different treatment therapies, it can tell doctors that a patient’s heart condition is getting worse, even before the patient feels any symptoms.

While having your personal health data online can be convenient, and in some cases, life saving, the one major concern is how secure and private your data can remain once it’s shared. The University of California, Los Angeles (UCLA) Health recently experienced a cyberattack, which may have compromised as many as 4.5 million patient records.

But online healthcare might be a case where the potential rewards will far outweigh the risk — the stakes are as high asthey can ever be when lives are at stake.

Today, there’s a lot of talk about bringing our everyday appliances online, a concept that’s commonly called the Internet of Things; Internet-connected refrigerators and washing machines are real products you can go out and buy right now.

The logical extension of that is surely when our bodies join the Internet of Things. With services like WellnessFX, devices like the CardioMEMS, and consumer wearables becoming more adept at tracking our everyday activity.



Wearables: Revolutionizing Medical Research   Leave a comment

The activity tracker you have on your wrist can do more than just count the number of steps you have taken and the hours you have slept. It has the power to change the way medical research is conducted.

MEDICAL RESEARCH IS A PARAMOUNT COMPONENT of medical studies and is crucial to our understanding to how people react to symptoms, how diseases work, and how effective a particular drug is in the real world.

One of the biggest challenges facing medical researchers is the lack of subjects. The truth is that methods for conducting medical research haven’t really changed in decades. Researchers would try to recruit subjects by putting up flyers, or attract them by offering small rewards for participation. In some cases, university might even make it compulsory for undergraduates to participate. Needless to say, these methods do not provide an accurate a cross-section of the population, thereby limiting our understanding of diseases.

Apple wants to change this. There are already hundreds of millions of iPhones out there and millions of users wearing Apple Watches and other activity trackers. So how can they harness this? The answer is ResearchKit, an opensource software framework that will allow researchers and developers to create apps for medical research.

n a nutshell, ResearchKit will allow researchers and doctors to gather more data by using apps and taking advantage of the millions of iPhones and Apple Watches that are already out there.

For example, one common way to assess Parkinson’s disease is the Parkinson’s Gait Test, where a doctor rates a patient on his walk on a scale of 0 to 4. It’s highly subjective and also troublesome to conduct as it requires patients or subjects to come in and walk in front of a doctor. But by using the accelerometer in the iPhone and Apple Watch, ResearchKit lets researchers and developers create apps that can accurately measure the gait of a patient or subject. It also lets subject do the test wherever they are and whenever they want.

Beyond Parkinson’s disease, ResearchKit will also allow for other apps to be created that can be used to measure and test for other conditions and diseases, allowing research subjects and patients to self-diagnose and take part in research without traveling to a clinic and without the presence and guidance of doctor. It makes things much more convenient and simpler.

Since ResearchKit pulls data out of the Health app, it’s not limited to just the Apple Watch, it will work with any wearable that uses an app that syncs with Apple Health – and that’s a list that includes popular wearables like Jawbone’s Up activity trackers, Withings Activité smartwatches and Polar’s running watches and activity trackers. This allows researchers to gather a larger, more diverse and meaningful amount of data.

Beyond Apple and ResearchKit, Google also wants to use wearables to advance medical research and studies. In June earlier this year, Google’s Google X research division announced a wristband that was
designed specifically for medical research. It will be more accurate than consumer grade activity trackers and it can measure heart rate, heart rhythm, skin temperature and even ambient light exposure and noise levels by the minute.

The intended use of this wristband is for doctors to prescribe them to patients or for use in clinical trials. in future, devices like Google’s wristband will be given to everyone, so that doctors can be alerted to problems and people can catch signs of diseases early.

Like Apple with ResearchKit, Google is hoping that its new wristband will let doctors track their patients more accurately and reliably, especially when they are away from hospital, thereby giving them deeper insights into their conditions and their lives, and also alerting them to any major complications before they can occur. The activity tracker you have on your wrist

Secure path to the Internet of Things   Leave a comment

With a seemingly countless number of connected devices, the Internet of Things (IoT) will be a gigantic growth market in the coming years. With the right solution, developers can concentrate on their core competencies and access the required specialist know-how in the shape of affordable, reliable and pre-validated modules.

The Internet of Things is growing steadily and rapidly. These intelligent objects have their own IP address and are constantly connected to each other over the internet,  making them able to communicate freely with each other. Sensitive data and devices must be protected from unauthorised access.

The first requirement for a network of machines and devices of any kind is secure IoT access. This can be provided either directly or via a gateway. In the first case, a gateway will already be implemented in the individual device. A protocol conversion between the internal and external network is often useful and necessary. Security is a complex issue and involves safety’ (broadly referring to safe operation) and ‘security’ (meaning safe from attacks by outsiders).

Intel quickly realised that this is a major obstacle for widespread access to the IoT. In cooperation with its subsidiaries Wind River and McAfee, Intel set out to develop a  secure end-to-end solution available from one source. This seamless and secure solution combines the individual products and special expertise from each company for selected platforms such as the Intel Atom-38xx family. Wind River supplies the Wind River Intelligent Device Platform XT which includes the operating system (Wind River Linux5.0), prevalidated software stacks, hardware drivers and matching libraries and tools. Functions such as administration, communication, connectivity and security as well as runtime environments such as Java, Lua and OSGi are all supported.

Fig 1 congatec’s current offering on the hardware and software sides of the IOT topology, with the Intel
processor selection on the left, and the matching form factors on the right.

iot topology

McAfee’s security software, McAfee Embedded Control, provides features such as dynamic application whitelisting (only registered and verified applications can run) and change control (all modifications of the code and the environment must be explicitly approved before execution). Intel provides the hardware platform itself plus hardware feature enhancements such as TPM (tamper proof module) and matching hardware-related software and stacks. The essential point here is that Intel validates the end solution as a whole; the complete processor board including all firmware.

Standard Modules

For those who neither want to rely on finished, commercially available devices nor go through the complicated and time-consuming process of certifying their own developments with Intel, the use of pre-certified function blocks makes good sense. Many industry sectors already use modular computer systems that are highly scalable for the specific application and based on proven standards such as Qseven or COM Express. The use of modules that are precertified for the Intel solution not only saves time and cost when implementing secure Internet connectivity, they also open up all the advantages of modular computer systems. Important criteria when selecting a module supplier includes support of the relevant standards, quality of the modules and the ability of the module manufacturer to effectively support the system manufacturer in the development of its own systems.

The the conga-QA3 Qseven module from congatec with processors from the Intel Atom E3800 family is particularly  well suited for connecting to the Intel Gateway Solutions for the Internet of Things. It enables the use of Intel Atom processors with up to four cores and clock speeds from 1.33 to 1.91GHz. Depending on the system and its application, the total power consumption ranges between as little as 4.5W to 12W. This enables the development of very economical and extremely powerful embedded PCs, that can be hermetically sealed and operate fan lessly in an extended temperature range. The maximum RAM size is 8GB DDR3L memory, and the integrated Intel HD graphics can support two independent Full HD displays via DisplayPort, HDMI or LVDS. Numerous interfaces and functions (including Gigabit Ethernet and USB3.0), enable fast and cost effective realisation of high-performance embedded systems with low power consumption such as Box PCs or other customised solutions.

Figure 2 - congatec's certified Intel Gateway Solution for the IoT

Fig 2 congatec’s certified Intel Gateway Solution for the Internet of Things

The combination of reliable hardware and a consistent software package, including everything from firmware to operating system and applications, provides a totally secure root of trust for IoT gateway applications. Thanks to outstanding performance, it is possible to carry out additional demanding tasks such as evaluation, consolidation, storage and visualisation of data, as well as sophisticated protocol conversions between the individual connection levels.

QSys is a modular embedded PC from TQSystems based on the Intel Atom E38xx. The combination of the MB-Q7-2 mainboard and thecongatec conga-QA3 module provides a highly compact embedded computer system and an ideal platform for use with the Intel Gateway Solutions for the Internet of Things.

The compact box design, with external dimensions of only 100x100x23mm³ and many interfaces and functions, is an example of how to quickly and cost-effectively implement a high-performance, passively cooled embedded system for gateway applications. Hardware security features such as TPM 1.2/2.0, the Sentinel HL Security Controller and integrated secure EEPROM enable the realisation of embedded systems with an exceptional level of security. The example has shown how quick and easy it is with congatec’s modular system to build concrete solutions for secure IoT gateways. The right know-how and technology can, however, bring further benefits. Thanks to the 70x70mm compact form factor of the Qseven module it is easy to transfer the system layout to a customised system, making the development of complete single board computer systems a simple and inexpensive task. The re-validation effort is relatively low because key components, such as processor, I/O system, network peripherals and firmware, require no or little modification. congatec has, for example, already implemented a complete mini- ITX single board solution.

As an ODM (Original Device Manufacturer) congatec can also develop complete customised systems and validate them for the customer, or use its know-how to help customers validate their own developments. The cost optimisation of this approach is particularly interesting where large production runs are concerned.

Modular systems consisting of pre-integrated hardware and software modules enable manufacturers of IoT-enabled systems to  develop secure solutions quickly and costeffectively, without having to deal in any detail with the complex security issues. On the one hand, security is safeguarded by a global player such as Intel bundling its expertise with that of its subsidiaries Wind River and McAfee in an end-toend, validated solution. On the other hand, they can rely on the manufacturer of the appropriate certified standard module, who is responsible for high manufacturing quality and practical support during the implementation of the complete solution. It is important to select the manufacturer carefully to avoid unwelcome surprises later on.

While current modules are primarily designed to provide gateway functionality for applications in the areas of industrial electronics, mechanical engineering, energy supply and transportation, subsequent modules and validation packages will cover additional functionalities and industry segments. The possibilities offered by the IoT are virtually unlimited and hold a rich potential for further development

Posted November 5, 2015 by Anoop George Joseph in Internet

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