How To Build Reliable, Responsive, Low-Cost Mobile WiFi Networks For The Industrial Internet of Things

How To Build Reliable, Responsive, Low-Cost Mobile WiFi Networks For The Industrial Internet of Things

In this video, Charles Chen, Country Manager for India, MOXA is going to talk about how to build a reliable, more responsive and low-cost mobile Wi-Fi Network for the Industrial Internet of Things (IIoT). He starts with an explanation of various challenges and applications of IIoT, what is it? And finally building a Wi-Fi network for IIoT.

Introduction of the speaker: Charles Chen is experienced in Business Development with Fortune 500 companies, having been a part of Project Management for Multi Million Dollar Projects. He has 15+ Years of experience in Industrial Communication and a Comprehensive knowledge of Product Marketing & Sales. AT MOXA he has held various positions over the years, starting as a Product Manager and Product Marketing Manager, and has held roles like Business Development Manager and Embedded Computing Business Manager.

 

06_How to Build Reliable, Responsive, Low-Cost Mobile WiFi Networks for the Industrial Internet of Things.mp4 from EFY on Vimeo.


 

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Microchip Simplifies The Development Of Smart, Connected And Secure Solutions With A Hardware Cryptography-Enabled Microcontroller

Microchip Simplifies The Development Of Smart, Connected And Secure Solutions With A Hardware Cryptography-Enabled Microcontroller

The CEC1702 full-featured microcontroller streamlines security implementation for an increasingly connected world

17 March 2017 [NASDAQ: MCHP] — The CEC1702 hardware cryptography-enabled microcontroller is now available from Microchip Technology Inc., a leading provider of microcontroller, mixed-signal, analog and Flash-IP solutions. The CEC1702 addresses the increasing need for security measures, such as secure boot, driven by the continual growth of Internet of Things (IoT) applications.

The CEC1702 is a full-featured ARM Cortex-M4-based microcontroller with a complete hardware cryptography-enabled solution in a single package. This low-power but powerful, programmable 32-bit microcontroller offers easy-to-use encryption, authentication, private and public key capabilities and allows customer programming flexibility to minimise customer risk. The CEC1702 also provides significant performance improvements when compared to firmware-based solutions. The device’s hardware cryptographic cipher suite reduces compute time by orders of magnitude over software solutions, and, as an example, provides 20x-50x performance improvement for PKE acceleration as well as 100x improvement for encryption/decryption. This robust hardware-based feature set results in applications that can run security measures quickly, effectively and with significantly lower cost and power consumption.

Protecting system integrity has never been more important. Whether it’s being used as a security coprocessor or a standalone microcontroller, the CEC1702 delivers a multi-dimensional defense against attacks, including:
· Pre-boot authentication of system firmware: Providing an immutable identity and a root of trust to ensure that the firmware is untouched and hasn’t been corrupted
· Firmware update authentication: Verifying that the firmware update has not been corrupted and is from a trusted source
· Authentication of system critical commands: Attesting that any system-critical command is from a known source with authorisation to make the given change, preventing potentially devastating actions
· Protection of secrets with encryption: Safeguarding code and data to prevent theft or malicious activities

“The acceleration of the Internet of Things has brought higher visibility to the security considerations of new designs,” said, Ian Harris, vice president of Microchip’s computing products group. “One of the hardest challenges to solve in a connected system is the ability to ensure that the boot code has not been comprised. The CEC1702 eliminates this issue by making it easy for designers to verify pre-boot authentication and then provide firmware updated from known, trusted resources.”

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SmartMoo, An Agri-IoT Revolution

SmartMoo, An Agri-IoT Revolution

Our daily diet includes dairy products in one form or the other, be it milk, ghee, butter or other milk based products. These play a very important role in maintaining the nutrient balance in our body. But, how do you know if the milk you drink is hygienic, with nutrients in proper portions, stored under correct conditions and is from a healthy cow? Definitely, a milk-packaging brand can answer these questions to some extent, but what about farmers, who have no idea about the milk’s quality or contents? They would not even know if they are getting paid proportional to the quality of the milk or if their cow is under-nourished.

Fig. 1: Activity meter on a cow

Milk is India’s largest crop—India alone produces about 155 million tones of milk annually, and this number can increase further if the emerging markets perform well. So to resolve this issue, how about a full-stack Internet of Things (IoT) company that provides end-to-end dairy solutions? Here, an end-to-end solution covers tracking and monitoring of animal health, automated milking system equipped with smart machines, smart milk procurement peripherals, real-time payments and chilling milk using bulk milk coolers.

This is what a team of five co-founders with combined 90+ years of experience have formulated. They are called Stellapps, and their creative product is called SmartMoo.

Spelling out SmartMoo

Fig. 2: SmartMoo milk production application—SmartMoo-Herdman

The innovative applications of SmartMoo use the IoT, Big Data, Cloud, mobility and data analytics to improve agriculture supply chain parameters like milk production, milk procurement, cold chain, animal insurance and farmer payments. Primary focus is on data application and smart learning, using smartSDP (service delivery platform)—the full-stack IoT solution to optimise dairy supply chain.

The IoT at the farm. Milk production-side IoT intervention includes sensors in the milking system. For example, an electronic milk meter monitors the functioning of milking machinery, animal wearables such as cow pedometers, radio frequency identification (RFID) ear tags and Android applications to scan and capture data from small farmers who cannot afford automation. This data from sensors is acquired by SmartMoo IoT router and in-premise IoT controller and transmitted to Stellapps SmartMoo Big Data Cloud SDP.

Over the Cloud. In Cloud servers, SmartMoo suite of applications analyses and crunches received data before disseminating the analytics and data science outcome to various stakeholders over low-end and smart mobile devices. Data acquired is used by Cloud-side analytics and machine learning algorithms for yield improvement, preventive healthcare, accurate oestrus detection, reducing inter-calving period, nutrition improvement, optimised animal insurance and reduction in the cost of operations. The data acquired at the milk production level by SmartFarms is used in the next hop of the supply chain.

At milk-collection centres. Milk procurement side includes sensors to analyse the milk quality, assess adulteration-limiting antibodies leaving the milk, assess the farmer’s performance and save solid not fat (SNF), fatty acids (FAT) details using the farmer’s RFID tags. The details are sent to the farmer via SMSes. Data acquired is used by Cloud-side applications to determine return on investment improvement, enhanced traceability, regional assessment of milk production pattern and automated real-time farmer payments.

At storage units. Milk cold-chain-side IoT intervention includes sensors for accessing milk temperature, volume of milk, energy optimisation and pilferage control. Data acquired is used by Cloud-side application to ensure adherence to the cold chain protocol, determine quality of milk and for preventive maintenance of milk-chilling equipment.

Putting agriculture and technology together

Agriculture, by default, is rural and remote. This causes troubles like remote management and difficulty in getting local expertise on premise. This is a major problem in emerging markets especially where farm productivity levels, quality of farm produce and production-side supply chain values are extremely low as compared to developed markets.

Stellapps team analysed this issue and found out that using sensors in the farms to automatically acquire data and apply analytics and machine learning on the Cloud and then using the outcome of the analytics and machine learning can solve both the issues efficiently.

Fig. 3: SmartMoo milk procurement application

A simple solution might be implanting a sensor on the milking equipment, storage units and pedometers, and deploying a milk-collection centre with milk-examining equipment. Connect all devices through the Cloud, collect data and send it to the dairy. However, this is not all.

Because the whole team were from IT and technology background, it took them a lot of time to understand agriculture and dairy verticals. “This lack of vertical experience was a disadvantage as well as an advantage. We were able to look at the problems from a fresh perspective,” says the Stellapps team.

The major problem was to get customers to appreciate the need and value of the product, and obviously the major customers, farmers and the rural crowd found it difficult to digest too much technology.

Once the farmers understood and accepted the need, the next challenge arose—remoteness of deployments made it hard for support and maintenance. This challenge has been overcome today by providing most of the support via Cloud interfaces and also via training customer support teams.

Another issue is that customers expect software Cloud services to be free, which is a problem the team is trying to surmount.

Fig. 4: The founding team behind SmartMoo (left to right: Ramakrishna Adukuri, Venkatesh Seshasayee, Ranjith Mukundan, Ravishankar G. Shiroor and Praveen Nale)

The bigger picture

The whole company is bootstrapped using a corpus from career savings of the founders. The founding team members have strong technology-industry experience and come from IITs. In addition to this, a good technology-centric idea made it easy to get funding from various alumnus including IIT-Madras/Rural Technology Business Incubator (RTBI). “We were lucky to run into Omnivore Partners, who had agriculture-technology-specific focus, and Stellapps’ business vision aligned with Omnivore’s,” says the team.

The whole system does not benefit the farmers and the company alone but also ensures end customers with good-quality products. “We are touching more than 350,000 farmers every day through our solutions and around 4.7 million litres of milk every single day,” the team adds.

The proprietary smartSDP platform and suite of apps touch close to two billion litres of milk annually. Proprietary solutions are deployed successfully at many private diaries in India, Kenya and Nepal as they continue to rapidly expand. Not just this, the response of SmartMoo users is also overwhelming—a lot of farmers from various districts of Karnataka like Kolar, Coorg, Mysore and others find SmartMoo very useful.

Through Stellapps technology solutions applied at the Nepal farm, there has been a substantial increase in productivity of the farm, touching 800 cattle, and the farm has been able to draw upon several thousands of litres of milk with clean milk technology and raise the health and monitoring services of cattle.

SmartMoo’s centre of gravity is shifted towards software/data on the Cloud, thereby commoditising the hardware. This Bengaluru based startup aims to create a major revolution in the agriculture industry by revamping the dairy farms to boost productivity.


Ankita K.S. is audience development editor at EFY, and secretary of IEEE-YP. She is an engineering graduate, and also writes articles on technology for electronicsforu.com

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LTE – A Continuing To Evolve Towards 5G

LTE – A Continuing To Evolve Towards 5G

When we talk about network evolution it is by no means all about 5G. Despite all the resources being poured into developing the technology for the next generation of mobile communications users, there are still new features that are being introduced to LTE-A which will continue to push performance boundaries up until and even beyond the launch of 5G services. Staying true to its full name (Long Term Evolution), the LTE/LTE-Advanced technology standards are still growing and evolving. New networks are still being rolled out, and leading-edge features are being added to 4G to satisfy the market need for ever-increasing data rates.

Evolving with 5G

There are three main ways in which LTE-A is evolving towards 5G. The first is by improving user throughput for small cells by the use of higher modulations schemes in combination with higher order carrier aggregation. Secondly, the ongoing improvements in interference, cell coverage and system throughput, are being achieved with the introduction of features such as CoMP (Coordinated Multipoint transmission/reception) and feICIC (further enhanced Inter-Cell Interference Coordination) which offer improvements in cell edge performance. The third one is the introduction of low complexity type user equipment (UE) for IoT applications, a development that is already happening under LTE-A with the introduction of NB-IoT as well as Cat-0 and Cat-M. These new protocols will place tighter specifications on systems signaling in requirements to accommodate large numbers of UEs.

The challenges

One of the major challenges for wireless network validation is to keep up with the increasingly and rapid introduction of new features in the roadmap of 3GPP LTE-A as we move through specifications that are already starting to look remarkably like some of the 5G targets. At its inception LTE used just a single 20 MHz carrier, and its performance only started to meet the IMT targets for 4G in real world scenarios when LTE-Advanced (LTE-A) features were progressively added to it. The first enhancement was carrier aggregation, which combines blocks of spectrum known as component carriers (CC), enabling the use of fragmented spectrum to increase data rates – initially combining two carriers (2CC) but now being introduced for up to 5CC, and also combining time division duplexing (TDD) and frequency-division duplexing (FDD) spectrum. Other features introduced were: Higher Order MIMO, which allows increased spectral efficiency to be achieved; Relays – which extend coverage in areas where wired backhaul is uneconomical; and Self-Organizing/Self-Optimizing Networks (SON), which enable the efficient use of heterogeneous networks (HetNets) that improve the coverage and capacity provided by traditional macro base stations.

Higher levels of modulation density, such as 256 QAM, have already pushed up the achievable data rate to 1.6 Gbps when used in combination with carrier aggregation and 4×4 MIMO. The aggregation of higher numbers of component carriers is pushing this still further: the highest downlink data rate theoretically available is 3.917 Gbps, which combines 256 QAM with 8×8 MIMO and 5CC aggregation.

Interference and implications

There was also a successive introduction of Interference Management (IM) functionality with increasing levels of sophistication, enabling increased area spectral efficiency to be achieved. ICIC (Inter-Cell Interference Coordination), which reduced interference at the cell edges, was first evolved to eICIC (enhanced ICIC), and to further enhanced ICIC (feICIC). eICIC and feICIC use a technique known as ‘cell range expansion’(CRE) to increase the coverage area and reduce interference at the cell edge of the smaller cells. These techniques allow users to be offloaded from the macrocell to the small cell, and are especially important when carrier aggregation into being used. Testing a network employing eICIC/feICIC requires the tester to apply the relevant mobile device measurement procedures in order to feedback correct and reliable information to the network.

CoMP was introduced to further enhance LTE-A performance. HetNets often do not deliver the expected user experience, mainly because of poor cell-edge performance due to the lack of traffic coordination and interference management between small cells and macrocells. CoMP coordinates transmission and reception between different transmitting and receiving cells through the use of load balancing, coordinated scheduling, and the management of signal power and interference. The tight synchronization needed between multiple transmitting and receiving points means that CoMP is challenging both to configure and to validate. Using realistic CoMP usage scenarios in both uplink and downlink when testing enables operators and vendors to perform lab and field trials incorporating realistic performance tests, and thus maximize throughput in their HetNet deployments.

The demands are huge

So what are the main challenges for testing the new features, as each is agreed? Physical layer performance will become more difficult to validate for massive MIMO at higher carrier frequencies, and this is equally a problem that will need to be solved before 5G can be introduced. Another challenge will be testing the fusion of multiple technologies within one system. Not only do features need to be tested in isolation, but crucially where applicable along with the interaction between those, for example testing downlink CoMP in combination with carrier aggregation, and LAA alongside higher order MIMO schemes. As the demand on the networks increases, testing needs to take place for significantly larger numbers of UEs, in order to ensure that the system and user KPIs are met when the network is loaded. This is particularly challenging at the cell edge where interference is prominent.

From a network test point of view, it is crucial that support for new features – and the interaction between them – is made available for R&D as soon as possible; so that network performance can be validated under realistic user scenarios before the features are introduced on real mobile terminals. As capacity becomes an even greater challenge, intelligent debugging capabilities are being developed to validate the system performance and specific of the stack under high load conditions. However as feature interaction and capacity testing place ever increasing demands on validation, it is important to provide KPI metrics that do not create ‘information overload’, but instead genuinely benefit testers and help them to identify where there is a performance bottleneck.


 

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Building Secure, Flexible IoT Platforms

Building Secure, Flexible IoT Platforms

This video os based on the talk that happened on the 13th of January at India Electronics Week 2016.

The IoT industry needs to develop organically and robustly through the work of a wide range of innovators and technologies. Therefore, understanding the underlying elements of an IoT platform and how they work together is fundamental to the success of this market. This session aims to give you an overview of the hardware and software components needed to build secure, flexible IoT platforms that address a wide range of applications, from sensors nodes to security cameras and beyond.

Presented by: Dr. Srinivas Mandavilli, Country Manager, Imagination Technologies

02_Bulding Secure, Flexible IoT Platforms from EFY on Vimeo.

KNOW THE SPEAKER: Dr. Srinivas Mandavilli is the Country Head of Imagination Technologies, for India. He has previously worked in various engineering management roles at Mentor Graphics, Hitachi and Motorola. Srinivas holds a BTech (EE) from IIT Chennai and a PhD (CS) from IISc. He has worked on a wide range of technologies including microprocessor architectures, embedded systems, scalable IP communications and EDA.


 

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