All posts tagged: data

The PubNub Data Stream Network enables developers to rapidly build real-time apps that scale globally, without worrying about infrastructure. PubNub enables you to easily build and scale real-time apps and connected data-stream services for home automation, Internet-of-Things applications, connected devices and just about anything else with APIs and support across a large range of different platforms, operating systems and programming languages.

Using PubNub’s extensive, friendly documentation, quick-start guides, APIs and building blocks, you can easily get started building your own real-time, connected apps very quickly – building an entire simple app in minutes, without worrying about cloud connectivity or infrastructure.

The aim of the PubNub system is to provide a real-time infrastructure and framework for developers to build real-time apps as easily as building a web page. The PubNub Realtime Network provides global cloud infrastructure and key building blocks for real-time interactivity, allowing developers to spend their time and effort on what they do best, creating brilliant real-time apps, without worrying about infrastructure challenges, but also providing users with the real-time information updates, real-time connectivity, interaction, communication and collaboration experiences that they expect from today’s apps and web services.

Key “building blocks” are provided to implement basic functions such as analytics, mobile support, security, storage, presence detection and push notifications in your app, allowing you to rapidly “plug together” cloud-connected application prototypes.

The system provides support and SDKs for over 50 languages and development platforms, including iOS, Android, JavaScript, .NET, Java, Ruby, Python, PHP, and many others, and supports a vast array of platforms and frameworks with easy-to-use APIs for mobile, browser, desktop, server, or embedded Internet-of-Things applications.

Furthermore, PubNub Presence allows real-time monitoring of devices and their presence in Internet-of-Things applications, and PubNub offers many other features that are particularly valuable in IoT applications. However, the capability that PubNub provides, allowing you to add real-time communications to your apps without worrying about infrastructure, and to stream, store, sync, secure and manage your data on all devices, everywhere, is valuable for applications in all kinds of mobile, desktop or browser-based environments – not only in Internet-of-Things applications.

As well as support for these languages and operating systems, PubNub provides support, documentation and SDKs to enable connectivity with many popular hardware platforms for embedded and IoT applications, such as Electric Imp, mBed and Raspberry Pi. This allows for low-cost prototype and final product development thanks to PubNub working with these open-source hardware platforms.

You can try PubNub free of charge, using a free sandbox account for demonstration, hacking or experimentation. A sandbox-level account allows you to build PubNub-based applications with up to 20 daily active devices, which should be more than enough to get you up and running. If you need support, the free sandbox-tier account also provides access to the PubNub community forums, and a “best effort” service-level agreement.

Of course there are also a broad range of paid account tiers available, allowing you to support the number of devices and amount of bandwidth that your application requires at an economic rate that can scale up and grow with your business.

Message payloads up to 32 kilobytes in size can be sent through PubNub, with a small fee per message applicable to paid accounts, charged on a varying scale depending on the message payload size you send and whether or not SSL encryption is required for your message traffic.

The PubNub Developer Portal gives you easy access to all of your usage metrics, and these metrics are updated at least once per day, allowing you to always get an up-to-date snapshot of your historical message traffic and usage charges.

PubNub’s global cloud infrastructure allows you to build and deploy real-time apps with a very robust level of scalability, reliability, performance and service guarantees. PubNub streams more than three million messages a second to 150 million devices per month, connecting every PubNub-enabled device and platform in the world with a latency of less than 250 milliseconds.

With replication across 14 data centres around the world, PubNub provides a very high level of service reliability, and building and deploying your real-time apps via PubNub’s global infrastructure provides your applications and services with that same level of reliability even when you’re scaling up to hundreds of thousands of concurrently connected clients.

Data streamed through the PubNub real-time network is instantly replicated to PubNub’s data centres around the globe to minimise latency for the end user, and multiple levels of redundancy and failover ensure that your PubNub-based real-time app solutions always work essentially anywhere with very low latency, even with millions of users.

PubNub allows you to send messages between mobile devices instantly, and allows you to send and listen to events within your app by using simple publish and subscribe API calls. You can subscribe to a channel with a simple API call, and once subscribed to a channel, simply use the Publish API, specify the channel name and the message you’d like to send in order to publish a message to a channel.

The fact that PubNub is built around a Publish/Subscribe model for real-time messaging and signalling makes PubNub ideally suited to collecting, collating and distributing information from Internet-of-Things networks, an application area where protocols such as MQTT that are also based around a publish/subscribe messaging model are increasingly popular.

Once again, all of this means there exists another option, another choice, another system to get your Internet-of-Things ideas from your notebook to reality. And doing just that with any system may seem like an impossible task.

However with our team here at the LX group, it’s simple to get prototypes of your devices based on the Arrayent platform up and running – or right through to the final product. We can partner with you – finding synergy with your ideas and our experience to create final products that exceed your expectations.

To get started, join us for an obligation-free and confidential discussion about your ideas and how we can help bring them to life – click here to contact us, or telephone 1800 810 124.

Published by LX Pty Ltd for itself and the LX Group of companies, including LX Design House, LX Solutions and LX Consulting, LX Innovations.

GroveStreams is a powerful cloud platform that provides storage and analytics for the Internet of Things, providing Big Data analytics in the cloud and allowing you to capture, analyse and make decisions on data as it arrives. This essentially provides powerful decision-making capabilities to many users and devices and allows you to easily aggregate, visualise and analyse data arriving from many different sensors and data sources.

The included data-streaming analytics are designed to scale to meet your demand for data, so that your business or organisation can quickly react to changes in the data environment – and changes in the physical sensor environment – as those changes are happening. GroveStreams isn’t just built to allow you react to data, it’s also built to allow your devices to react accordingly by using the open, platform independent, GroveStreams API.

The proliferation of devices that generate data in wireless sensor networks, environmental sensing, home and building automation, and Internet-of-Things applications and systems increases every day, and GroveStreams offers a system that can effectively capture, analyse and react to these emerging Big Data sources in a timely manner, with cloud-based scalability and reliability.

GroveStreams is an open cloud-based platform that any organisation, user or device can take advantage of, with an open API and free accounts for low-traffic hobbyist, experimenter or evaluation users. The platform specialises in capturing, analysing and acting on large amounts of time-series data points and streams, with the ability to manage large numbers of different data streams for each organisation.

Each stream can store over 60 million data points or samples, meaning that a stream of sensor data collected once per second can be logged continuously for just under two years in a single continuous data stream.

The GroveStreams platform provides sample timing accurate to the millisecond, and support for many different data types such as integers and floating-point numbers with user-defined physical units, text strings, dates and times and geographic coordinates, along with actionable data analytics such as user-defined roll-ups of data over time, interval gap detection to allow you to monitor the quality and reliability of sensor data streams as they arrive, data streams that are derived from internal or external RSS feeds, calculations and basic statistical processing on data streams, and derived data streams that are derived from arithmetical or statistical operations on other streams of sensor data.

For example, a stream of temperature data in degrees Fahrenheit may be generated by taking another data stream which receives temperature measurements in degrees Celsius from a sensor and applying a mathematical transformation to this stream, or a stream of energy use data from an energy sensor might be multiplied by another stream containing real-time energy pricing information (cents per kilowatt-hour) derived from an RSS feed, allowing an accurate measurement of accumulated energy cost.

GroveStreams provides for the easy aggregation of large numbers of different data streams, and customisable drag-and-drop HTML dashboarding for flexible, customisable dashboarding and visualisation of your data streams, along with live charts and grids which can be embedded within external Web pages, allowing embedding of data displays within external web pages – although they are still served from the GroveStreams cloud infrastructure.

New components and streams can register themselves automatically and appear in existing dashboards and aggregation analytics as they upload their initial feed data, minimising the need for difficult configuration of new components and streams to connect them into existing dashboards or analytics.

All components and streams provide their own RSS feeds, and RSS feeds can be added to your custom dashboards for viewing within the dashboards. It is also possible to configure sensor-driven, data-driven event monitoring with customisable HTTP call, email or SMS notifications – in response to sensor readings and data values, or in response to time-series trends and statistics derived from your data.

GroveStreams also provides Maps functionality, allowing you to spatially map your data from networks of devices that are equipped with GPS or other capability for location awareness. Distances between devices, speeds, and locations can be tracked and mapped, as well as being subject to all the processing techniques applicable to other data streams. And by providing user role-based security, with public/private web UI settings, you can make your organisation accessible to only your users or also to anonymous guest users, with the ability to set guest access rights to control the way that public users work with your data.

Futhermore a RESTful API is provided with almost all the functionality of GroveStreams exposed out via the public API, including fine-grained API access security. Basic examples to get you started with the API are provided for use with Java, Python, and even for use with Ethernet-enabled Arduinos, allowing you to easily get started with cloud data connectivity from your sensors and physical devices.

A fully browser-based user interface is provided, entirely in HTML without plugins such as Flash, allowing flexible, convenient use of the browser interface across all mobile devices such as smartphones and tablets. GroveStreams can even be re-branded as your “own” application provided to your commercial customers, with your own look, feel and brand identity – while all the cloud infrastructure and hosting under the bonnet is handled by GroveStreams.

GroveStreams is free for small users. Large users will only be billed for what they use (the number of transactions, the number of streams, etc). Once a user’s account exceeds the free metric amounts, they will be required to register a credit card with their account. Billing metrics are constantly gathered and can be monitored in an organisation owner’s account page. For users who aren’t organisation owners, it’s free.

Anyone who needs to collect large amounts of time-series data, monitor it, analyse it and react to this data or data from other devices quickly could benefit from connectivity to the GroveStreams service. Whether you want to monitor one data stream from a single source or many more streams from many sources, GroveStreams is likely to be useful for many different users, including utilities, sensor/device driven organisations or businesses that would benefit from near-real-time sensor data collection and analytics in the cloud. With accounts provided completely free for small-scale users, GroveStreams is also an attractive and accessible platform for electronics hobbyists, open-source enthusiasts and Arduino users looking to get started with a cloud service for data storage, analytics and visualisation for networks of Internet-of-Things sensors and devices.

And thus the possibility of harnessing the Internet of Things is made possible once again by a new platform with many possibilties. Here at the LX Group we can partner with you – finding synergy with your ideas and our experience to create final products that exceed your expectations.

To get started, join us for an obligation-free and confidential discussion about your ideas and how we can help bring them to life – click here to contact us, or telephone 1800 810 124.

Published by LX Pty Ltd for itself and the LX Group of companies, including LX Design House, LX Solutions and LX Consulting, LX Innovations.

The new Wi-Go system from Avnet is a complete development, prototyping and experimentation platform aimed primarily at wireless data acquisition, wireless sensor networks, automation and Internet-of-Things applications – based on the Freescale Freedom Development Platform for Freescale Kinetis microcontrollers.

Avnet Wi-Go offers designers a complete solution for developing real-world IoT applications by combining Freescale’s Xtrinsic sensor technology with a powerful Kinetis-L microcontroller and an embedded Wi-Fi module.

The Wi-Go system adds Wi-Fi capability to the Freedom platform and includes a built-in 800 mAh lithium-polymer battery which can provide up to days of power for portable, wireless data acquisition from the platform’s on-board suite of sensors, along with an on-board flash memory IC to facilitate data storage and provide additional storage for things such as complex webpages which may be served up from the Wi-Go board, providing a powerful and flexible wireless sensor platform at a low cost.

To keep initial cost low, the Avnet Wi-Go is a two-board set comprised of a Freescale Freedom development board mated to an Avnet Wi-Go module. No other components arerequired to get started developing your own Internet-of-Things products and devices. The Freescale Freedom development platform is a small, low-power, cost-effective evaluation and development environmenbt aimed at quick prototyping and demonstration of applications of the Kinetis microcontroller family.

The Kinetis family offers an easy-to-use mass-storage device mode flash programmer, a virtual serial port and classic programming and run-control capabilities. The Wi-Go wireless accessory module extends this platform with a powerful suite of sensors, integrated battery and USB charging system, and wireless networking to meet an increasing demand for wireless sensor systems, portable data acquisition and connected, battery-powered Internet-of-Things applications.

The Wi-Go platform’s flexible sensor suite includes Freescale’s MMA8451Q accelerometer for 3D acceleration sensing, the MAG3110 low-power digital 3D magnetometer sensor for magnetic heading sensing, the Xtrinsic MPL3115A2 barometric pressure sensor, which provides pressure, altitude and temperature information, Vishay’s TEMT6200 ambient light sensor for light level sensing, a MAX8856 and MAX8625A for the power supply subsystem, including battery monitoring and smart charging, power management and efficient buck-boost regulation to maximise the system’s battery life.

These sensors are combined with the Kinetis KL25Z128VLK4-Cortex-M0+ microcontroller, operating at up to 48 MHz with 128 kb of flash and 16 kb of SRAM along with a full-speed USB controller and support for the sophisticated and open-standard OpenSDA USB serial and debugging interface, alongside Murata’s LBWAIZZVK7 Wi-Fi radio module, which is based on the Texas Instruments CC3000 SimpleLink 802.11b/g chipset.

As the WiFi communication hardware of the Avnet Wi-Go system are based on the CC3000 chipset, it supports TI’s SmartConfig network configuration tool, allowing easy configuration and provisioning of the wireless network settings for new Wi-Go devices on the network simply by using the SmartConfig app freely provided by TI on a smartphone connected to the wireless LAN.

The Wi-Go platform is also equipped with a S25FL216K low-power, 2 megabyte serial flash memory, flexible power supply options, a capacitive touch “slider”, an RGB LED and three discrete user LEDs as input and output devices for user interaction. The Wi-Go board also provides expansion I/O pins in a form factor that accepts Arduino-compatible “shields”, making it compatible with a rich ecosystem of third-party expansion hardware.

Example code is provided to set up a filesystem on the flash memory or to communicate with the flash in binary mode, along with other working code examples and libraries for communication with each of the other sensors, peripheral devices and WiFi radio present on the board.

Reference code and examples are provided to implement full end-to-end Internet-of-Things applications with Web services such as Exosite – for example using the TI SmartConfig app to configure wireless network connectivity, using cloud services client connection code to send data up to Exosite on the web, and streaming this data over the Web to an Android application which performs fusion of different sensor data and displays its results. It’s easy to get started logging sensor measurements on a Web service, for example, or to use a Web service to remotely select the colour of the RGB LED on the Wi-Go board.

A free cloud-based compiler is provided with each development board purchased, along with a free Freescale Xtrinsic sensor fusion toolbox application and a free connection to Avnet’s Exosite cloud services for up to two of your devices. A series of several videos is also offered by Avnet, outlining the capabilities of the Wi-Go platform in order to assist designers in creating Wi-Go based wireless applications.

These videos cover topics such as Xtrinsic sensor fusion on the Wi-Go platform, cloud capabilities of Wi-Go, and Web server and network configuration for Wi-Go. Finally, the Wi-Go platform is open-source, and designers have access to all design files and source code, which is an attractive feature for engineers looking to reduce the time to market for products and systems developed for Internet-of-Things applications.

And that is always one of the main goals of IoT product development – time to market. If you have a great prototype or idea – and need to take it to the market, our team of engineers can help you in all steps of product design, from the idea to the finished product. To get started, join us for an obligation-free and confidential discussion about your ideas and how we can help bring them to life – click here to contact us, or telephone 1800 810 124.

Published by LX Pty Ltd for itself and the LX Group of companies, including LX Design House, LX Solutions and LX Consulting, LX Innovations.

When it comes to developing Internet-of-things systems, a lot of public focus is placed on the hardware and networking infrastructure required to make it a physical reality. However when designing a system, the processing and analysis of collected data requires an equal or increased effort – and anything that can make this easier or more cost-efficient is necessary.

One example of efficient data processing for the Internet-of-things can be provided by the Amazon Kinesis – a new managed service for real-time processing of streaming data at massive scale, adding big-data services to the Amazon Web Services line-up.

Kinesis can collect and process hundreds of terabytes of data an hour from hundreds of thousands of sources, allowing you to write applications that process information in real time from all sorts of different data sources.

Data can be harvested from almost anything- such as sensors and instruments, user interfaces, or other sources of data. Let’s take a quick look at Kinesis and its potential role in Internet-of-Things applications.

Kinesis service accepts real-time data, replicates it and delivers it to applications running on Amazon’s cloud, allowing applications to tap big data in real time. Real-time operations on large amounts of data made possible by Kinesis enable you to collect and analyse information in real-time, answering questions about the current state of your data without waiting.

With Kinesis, developers can get more creative about what to do with large amounts of data flowing in live, and developers building applications on Amazon’s cloud services can now more easily take advantage of sensors collecting data, which is an important development for realising the potential of large-scale analytics on data collected from Internet-of-Things networks.

This certainly makes Amazon Web Services an attractive choice for developers seeking to put large scale data collected from sensor networks to work in the cloud.

The system can be scaled elastically for real-time processing of streaming data on a large or small scale, taking in large streams of data records that can be consumed in real time by multiple data-processing applications running on instances of Amazon’s Elastic Compute Cloud (EC2).

Data-processing Kinesis applications use the Amazon Kinesis Client Library, and these applications can read data from the Kinesis stream and perform real-time processing on the data they read. The processed records can be emitted to dashboards, used to used to generate alerts, or emit data to a variety of other Amazon big data services such as Amazon Simple Storage Service (S3), Amazon Elastic MapReduce (EMR), or Amazon Redshift.

Interoperability and compatibility with existing, established Amazon cloud computing services and products is an important factor which is likely to give the uptake and usability of Kinesis a significant advantage for established Amazon Web Services users. Kinesis applications can also emit data into another Kinesis stream, enabling more complex data processing.

With Kinesis applications, you can build real-time dashboards, capture exceptions and generate alerts, output data to drive user interactions, and output data to Amazon S3, DynamoDB or other cloud computing services.

Kinesis makes it possible to respond to changes in your data stream in seconds, at any data scale – for example, in Internet of Things applications, such a response may take the form of activating a certain device or automation system in a specified way.

You can create a new stream, set the throughput requirements, and start streaming data quickly and easily. Kinesis automatically provisions and manages the storage required to reliably and durably collect your data stream.

Kinesis will scale up or down based on your needs, seamlessly scaling to match the data throughput rate and volume of your data, from megabytes to terabytes per hour.

This allows your systems to reliably collect, process, and transform all of your data in real-time before delivering it to data stores of your choice, where it can be used by existing or new applications. Connectors enable integration with Amazon S3, Amazon Redshift, and Amazon DynamoDB.

Kinesis provides developers with client libraries that enable the design and operation of real-time data processing applications – a new class of big data applications which can continuously analyze data at any volume and throughput in real time.

Kinesis is cost effective for workloads of any scale – you can pay as you go, and you will only pay for the resources you use, like with other Amazon cloud computing services. Initiall you can start by provisioning low-throughput streams, and only pay a low hourly rate for the throughput you need.

Kinesis enables sophisticated streaming data processing, because one Kinesis application may emit Kinesis stream data into another Kinesis stream. Near-real-time aggregation of data enables processing logic that can extract complex key performance indicators and metrics from that data.

Complex data-processing graphs can be generated by emitting data from multiple Kinesis applications to another Kinesis stream for downstream processing by a different Kinesis application. You can use data ingested into Kinesis for simple data analysis, real-time metrics and reporting in real time.

For example, metrics and reporting for system and application logs ingested into the Kinesis stream are available in real time, allowing data-processing application logic to work on such data as it is streaming in, rather than wait for data bunches to be sent to the data-processing applications later.

Data can be taken into Kinesis streams, helping to ensure ensure durability and elasticity. The delay between the time a record is added to the stream and the time it can be retrieved is less than 10 seconds – in other words, Kinesis applications can start consuming the data from the stream less than 10 seconds after the data is added – this is useful in applications where real-world actuation or control of automation devices needs to happen relatively quickly.

By using such a powerful and scalable system such as Kinesis, you can get the power you need without paying for surplus processing capacity – but still have reserves ready on demand. But how to get started with Kinesis and your Internet-of-things plans?

Simply join us for an obligation-free and confidential discussion about your ideas and how we can help bring them to life – click here to contact us, or telephone 1800 810 124.

Published by LX Pty Ltd for itself and the LX Group of companies, including LX Design House, LX Solutions and LX Consulting, LX Innovations.

JSON, or JavaScript Object Notation, is a lightweight open standard format that uses human-readable text to transmit data objects in the form of pairs of attributes and values. It is used primarily to transmit data between a server and a web application as an alternative to formats and languages such as XML for lightweight, flexible formatting of data for Internet communication in a way that is both machine-readable and human-readable.

Let’s look briefly at how JSON can be used, how it compares to XML (Extensible Markup Language), and the role JSON can play as a lightweight format for information transport in Internet of Things and embedded applications. In an Internet-of-Things application, every “Thing” connected to the network should have an API that allows access to key data elements.

This data needs to be streamed at an appropriate rate over the Internet to a server directly, or to a gateway or other device in the local network. Near-real-time access to sensor data at the gateway or at the server allows contextual information derived from that data to be served up in a timely manner, so minimising network overheads is clearly valuable.

Although originally derived from the JavaScript scripting language, JSON is a language-independent data format and code for parsing and generating JSON data is readily available in a large range of programming languages, making it easy to get up and running with the language of your choice. JSON objects are human readable – they are basically freeform text documents. Whilst JSON objects contain rich information and are a highly flexible way to represent data, they are easy for programmers and database administrators to use.

XML is well established as a language of choice to describe structured data and to serialise objects, and various XML-based protocols exist to represent the same kind of data structures as JSON for the same kind of data interchange purposes. When data is encoded in XML, the result is typically larger than an equivalent encoding in JSON, mainly because of the presence of closing tags in XML.

While the API is a key consideration in implementing a RESTful solution for moving around and accessing your data, the format of the payload is also equally as important. XML is one traditionally popular language in these sorts of applications, but JSON is not as verbose as XML and does not contain detailed processing instructions. Being a more lightweight data interchange format, it is faster to use JSON to send bits of data, such as data from a sensor for example, around the Internet of Things.

JSON is promoted as a lower-overhead alternative to XML, providing similar data exchange capabilities with support for creation, reading and decoding of data in the real world with lower overhead. The increasing popularity of REST over SOAP in modern APIs also promotes greater use of and support for JSON as the preferred data exchange format, since you are no longer limited to only returning XML.

JSON-RPC is an RPC protocol built on JSON, as a replacement for XML-RPC or SOAP. It is a simple protocol that defines only a handful of data types and commands. JSON-RPC allows for notifications – information sent to the server that do not require a response – and for multiple calls to be sent to the server that may be answered out of order. This flexibility in choosing messaging options to get the data where it is needed with the priority that is needed in the most lightweight possible way is attractive in resource-constrained and bandwidth-constrained Internet-of-Things networks or embedded systems.

Modern web browsers incorporate native JSON encoding and decoding, increasing performance due to the fact that functions no longer need to be parsed as well as eliminating potential security vulnerabilities where JSON is evaluated as Javascript. Native JSON is generally faster compared to the JavaScript libraries used in the past to parse JSON, as well as more secure.

As an example of JSON in use for an existing embedded Internet-of-Things solution, the “Razberry” platform. This adds the hardware required for the Z-wave wireless home automation protocol to the Raspberry Pi single-board computer, turning an inexpensive device into a Z-wave home automation gateway and exposing control of your home automation network via a JSON interface.

Furthermore Google BigQuery added support for JSON a few years ago, explicitly mentioning the potentially useful role of JSON in connecting data collected from sensor networks and the Internet of Things to BigQuery, bringing the power of Google’s Big Data manipulation expertise together with the Internet of Things and sensor networks as the sources for that Big Data.

JSON is one of many tools available in the Internet-of-things toolbox, and can easily be used with many applications. And here at the LX Group our engineers have an excellent understanding of the standards required for effective communciation between devices within Internet-of-things platforms, and are ready to integrate it with your new and existing products.

To get started, join us for a confidential discussion about your ideas and how we can help bring them to life – click here to contact us, or telephone 1800 810 124.

Published by LX Pty Ltd for itself and the LX Group of companies, including LX Design House, LX Solutions and LX Consulting, LX Innovations.

Recently Google announced their new Cloud Platform services, which allow almost anyone to build applications, websites, store and analyse data using Google’s infrastructure. This is an exciting development for those looking to implement a scalable Internet-of-things system at a minimal cost – so we’ll take an overview of the system as it stands today.

Almost everyone is aware of the researched information, computing power and infrastructure available for Google’s myriad of services, and now it’s possible to harness some of this for your own needs. With the introduction of their “Cloud Platform”, you can harness this power that Google has used internally for years to provide Google’s familiar high-speed, high-scale big-data products and services such as Search, YouTube, Google Docs and GMail and make it available as cloud computing services for use with your own Internet-of-Things projects.

Large-scale, high-speed, distributed “cloud” storage and computation with large amounts of data is at the heart of everything that makes Google what it is, so it’s clear that they have substantial opportunities to offer external cloud-computing customers.

Whilst Google is not the first major player in the cloud computing market, their substantial infrastructure and “Big Data” experience represents a significant source of potential competition with other established cloud computing providers such as Amazon Web Services. The capability to use Google’s data centre infrastructure for cloud storage and computation, their data tools such as BigQuery to process very large scale data sets – and integration with Google’s data, services and apps are increasingly attractive.

The Google Cloud Platform is made up of a couple of different core components – Compute and Storage being two of the most important. The Compute component includes the Google Compute Engine, which is an Infrastructure-as-a-Service platform designed to run any application on top of Google’s infrastructure – which offers fast networking, scalable processing and storage, and the App Engine, a platform for developing and hosting web applications. The Storage component includes Google Cloud Storage and the BigQuery large-scale query system.

As with most cloud computing platforms, end users access cloud-based applications and infrastructure through a relatively lightweight local computer – via a web browser, lightweight desktop software, or a mobile device application – with the data and most of the software are stored on remote servers in the cloud. Therefore, the hardware requirements for the user to leverage the power of applications and data on Google Cloud Platform-hosted applications and services are almost trivial.

Many components of the Google Cloud Platform support open standards and protocols such as REST-based APIs. The Google Compute Engine is built atop a JSON RESTful API which
can be accessed via numerous different libraries, command-line utilities and GUI front-end tools. Google’s BigQuery, a cloud-based fully managed interactive query service specifically designed for work with massive datasets, is operated via an SQL-like query language.

Google Cloud Storage complements the Compute component of the Google Cloud Platform and serves to glue together all Google Cloud Services. Google Cloud Storage is a HTTP service that serves data directly over HTTP with high performance and resumable transfers of objects up to the terabyte scale. It offers support for two different APIs – one that is compatible with the XML standard used by competing providers such as Amazon Web Services and another API built around JSON and OAuth, consistent with the Google Compute Engine’s API.

The Google App Engine is a “Platform-as-a-Service” cloud computing platform for the development and hosting of web applications in Google’s managed data centres. Applications are sand-boxed and distributed across multiple servers. One of the major benefits of using the Google App Engine is that it can offer automatic scaling for web applications – that is, automatically allocating more resources for the web application to handle the increased demand as the number of requests for a particular application increases.

All that sounds quite useful, however why would your organisation use the Google Cloud Platform? Whilst it requires an initial investment to import your data (especially on a large scale) into the cloud, this is offset by the substantial advantages offered by the platform. By offering fully managed services that remove the requirement for upfront capacity planning, provisioning, constant monitoring and planning software updates. This can significantly reduce the total cost of ownership of large-scale data handling solutions.

Furthermore there’s one thing in particular that sets the Google Cloud Platform apart – the network that connects the company’s data centres so data can be processed and delivered where it is needed in milliseconds. Google has a private distributed backbone between all its data centres – so if you’re moving data around within Google’s cloud, even within geographically diverse data centres (although this is essentially invisible to the user) your data travels over Google’s backbone, and not over the Internet – providing substantially improved performance.

Whilst the Compute and Storage components of the Google Cloud Platform are separate offerings, the performance of Google’s networks make it appear as though they integrated seamlessly, thus allowing integration of Google’s cloud storage and computation with no obvious slowdown.

At the LX Group we have a wealth of experience and expertise in the IoT field, and can develop new or modify existing hardware and software to integrate your system with the Google Cloud Platform. As always, our goal is to find and implement the best system for our customers, and this is where the LX Group can partner with you for your success.

We can create or tailor just about anything from a wireless temperature sensor to a complete Internet-enabled system for you – within your required time-frame and your budget. For more information or a confidential discussion about your ideas and how we can help bring them to life – click here to contact us, or telephone 1800 810 124.

Published by LX Pty Ltd for itself and the LX Group of companies, including LX Design House, LX Solutions and LX Consulting, LX Innovations.

In this instalment in our series of articles focusing on various Internet-of-things systems, we explore the new Nearbus Open IoT Project. Although not the most complex of systems, Nearbus offers a level of control and interaction with devices and sensors which is ideal for demonstrations, proof-of-concept designs or even simple products where rapid development and low-cost are the main requirements.

Unlike other systems, Nearbus takes a different approach to device control. After loading the Nearbus on the device’s microcontroller, it is considered to be part of the “cloud” and as such transparent to the web services or API. In other words, you can read or write to the MCU’s registers directly from the cloud – which makes control much simpler than other systems. By “virtualising” the hardware in the cloud, it makes it much easier for existing services to interact with the real hardware, and in a more secure manner. Let’s examine the how this is possible with regards to the required hardware and software

Hardware – Due to market forces and age of the system at the time of writing, the Nearbus system only works with the Arduino-Ethernet platform. Thus the end microcontrollers used are Atmel ATmega328 programmed with the Arduino boot loader and interfaced with the Wiznet W5100 Ethernet controller. However this allows you plenty of GPIO, ADCs and CPU speed to complete a variety of tasks, and due to the open-source licensing of the Arduino platform the hardware cost for around A$20 per unit in volume. The main downside to this solution is the inability to use onboard WiFi chipsets, so the agent hardware needs to be connected to a separate WiFi router for true wireless control.

Software – Due to the current hardware requirement, the only code for each Nearbus node is their sketch (code) and the Arduino boot loader – both of which are totally open-source. The rest of the work is in interfacing your own cloud- or server-based applications with the Nearbus hub system. This transfer takes place via HTTP requests.

There are two methods for interfacing applications with the Nearbus system. The first method is the “transparent” mode which allows the agent to send and receive a packet of data over preconfigured periods of time, for example every five or ten seconds. This allows your cloud applications to call functions on the agent hardware as if it was controlling the MCU directly.

The second method is the “VMCU” mode (Virtual Microcontroller) which allows direct control of the basic MCU features such as GPIO, ADC, etc., via a web services API. This is the more complex method that maps the MCU remotely and thus allows direct control of the MCU’s registers and returns data in the raw from for your own web app to work with. The ability to map the registers removes a layer of complexity from the user or designer – as they don’t have to worry about network protocols, instead just be concerned with the microcontroller itself.

Furthermore you can configure, add and remove devices with a web-interface, and also create connections to send data to other IoT services such as cosm or twitter. If you don’t have a server capable of running your own web apps to interface with Nearbus, you can use other free or paid services such as Google Spreadsheet web apps – and demonstrations have been provided to show how easy it is to display, capture and analyse data from the hardware agent.

The Nearbus system is a different paradigm to the usual IoT systems. It may seem awkward or different to more conventional or consumer-oriented ways of doing things, however if you have a strong PHP and networking background it can be implemented easily with your server and applications. Due to the low hardware cost it’s ideal for monitoring or remote-control applications that don’t require complete real-time interaction.

If you’re interested in moving forward with your own system based on the Nearbus, we have a wealth of experience with the required hardware options, and the team to guide you through the entire process – from understanding your needs to creating the required hardware interfaces and supplying firmware and support for your particular needs.

Our goal is to find and implement the best system for our customers, and this is where the LX Group can partner with you for your success. We can create or tailor just about anything from a wireless temperature sensor to a complete Internet-enabled system for you – within your required time-frame and your budget. For more information or a confidential discussion about your ideas and how we can help bring them to life – click here to contact us, or telephone 1800 810 124.

Published by LX Pty Ltd for itself and the LX Group of companies, including LX Design House, LX Solutions and LX Consulting, LX Innovations.

Continuing from our previous articles which are focusing on a range of currently-available Internet-of-Things systems, we now move forward and explore another addition to the Internet-of-Things marketplace in more detail – the system known as “ThingSpeak”. Considered to be one of the first openly-available IoT platforms, ThingSpeak operates on their own free server platform, or you can run the software on your own personal servers – and as the entire system is open-source, it’s easier to work with and customise.

As with the other systems examined, ThingSpeak gives your devices the opportunity to interact with a server for simple tasks such as data collection and analysis, to integration with your own custom APIs for specific purposes. Due to the open-source nature the start-up cost can be almost zero, and unlike other systems ThingSpeak is hardware agnostic – giving your design team many hardware options. However as always, let’s consider the main two components in more detail.

Hardware – You don’t need to purchase special base units or proprietary devices. As long as your hardware is connected to the Internet and can send and receive HTTP requests – you’re ready to go. For rapid prototyping, examples are given using many platforms including netduino, Arduino, mbed, and even with the competitive Twine hardware. This gives you a variety of MCU platforms from Atmel and ARM Cortex providers to work with, and as these development platforms are either open-source or inexpensive, your team can be up and running in a short period of time.

Furthermore creating your own devices can be quite inexpensive – a simple device based on an Atmel AVR and Ethernet interface can be manufactured for less than $20 in volume, and doesn’t require any software licensing expenses. To save on hardware costs, it could be preferable to have various sensors in a group communicate back to one connected device via inexpensive Nordic NRF24L01 wireless transceivers – and the connected device can thus gather the data into the require fields for transmission back to ThingSpeak.

Software – Thanks to the open-source nature of ThingSpeak either working with the existing server software or creating your own APIs isn’t a challenge. Interaction is easy with simple HTTP requests to send and receive data, which has a useful form. Each data transmission is stored in a ThingSpeak “channel”. Each of these channels allows storage and transmission of eight fields with 255 alphanumeric characters each, plus four fields for location (description, latitude, longitude and elevation – ideal for GPS), a “status update” field and time/date stamp. Data sent over the channels can be public or private – with access via your own devices and software finalising the security.

Once sent to the server this data can be downloaded for further analysis, or monitoring using various HTTP-enabled entities – from a simple web page, mobile application or other connected device. Various triggers can be created to generate alerts for various parameters, and can be sent using email, twitter, or other connected services such as an SMS gateway. After being in operation for almost three years, the platform has matured to a reliable service that has exposed many developers to its way of doing things, so support and documentation is becoming easier to find.

Overall the ThingSpeak system offers your organisation a low barrier to the Internet of Things. Creating a proof-of-concept device or prototype hardware interface can be done with existing or inexpensive parts, and the use of ThingSpeak’s free server can make an idea become reality in a short period of time. And once you device on the service, by internalising the server software, you can have complete control and security over your data.

If you’re interested in moving forward with your own system based on the ThingSpeak, we have a wealth of experience with the required hardware options, and the team to guide you through the entire process – from understanding your needs to creating the required hardware interfaces and supplying firmware and support for your particular needs.

Published by LX Pty Ltd for itself and the LX Group of companies, including LX Design House, LX Solutions and LX Consulting, LX Innovations.

As the “Internet of Things” becomes increasingly prevalent this year, much has been written and systems devised to allow all manner of data to be gathered, analysed and devices controlled via wireless data networks. However these systems aren’t limited to items of a technological nature, as the broad IoT can also be of great benefit to primary producers and agriculture of almost any type. But how?

It’s simple – if more data about a particular item of interest is available, you can make better decisions concerning that item. If that data was available in real-time, you can make informed decisions faster. Let’s consider four areas in the farming arena that can benefit from this technology with some example possibilities.

Horticulture – There’s much more to achieving profitable returns on horticulture than just planting a seed and hoping it will grow. Apart from monitoring the weather – wireless sensors can be used to monitor soil temperature and moisture (even for multiple depths), greenhouse temperature and humidity, leaf wetness levels, solar radiation, and rain levels. Real-time data from these types of sensors can be useful to change crop maintenance procedures from regularly-scheduled to “when required” – saving time and money. Furthermore as data is gathered over time, more accurate predictions can be made with regards to crop success with regards to external factors.

Livestock – The monitoring of livestock is crucial, especially for expensive breeds that require a higher level of maintenance. Tracking individual beasts via a GPS connected to a local wireless network makes it easy to locate animals in a hurry, alarm you if one or more range too far from home – or if one hasn’t moved during the day, which could either mean an animal has become injured or isn’t getting enough exercise. With RFID technology counting and tracking the animals individual statistics from birth to sale becomes faster and simpler. Furthermore as animals come and go the hardware can be reused for new births or acquisitions, reducing recurring costs and further hardware investment.

Security – This is often overlooked due to the nature of the prevailing surroundings and personal relationships built over generations. However as the rest of society has an increasing number of unsavoury elements, so too does the agricultural sector. There are many ways to keep track of assets, such as: adding GPS tracking devices to expensive machinery; intrusion-monitoring sensors to sheds, gates, pump boxes and greenhouses; ultrasonic motion sensors to detect vehicle movement on out of the way tracks and access roads; tank water level sensors can detect when the level drops too quickly – alerting you of a leak or water theft; and closed circuit television cameras are now digital, and can send images that are legible during day and night allowing monitoring of any asset of interest – as well as record passers-by helping themselves to popular vegetable crops.

Water management – In some areas the supply of water is costly. As water rights are reduced and transport costs increase, monitoring water use and wastage is crucial. Water levels can be monitored across all storage tanks, flow sensors can monitor creek and river water movement and speed, and with data from soil moisture sensors, your system can supply the minimum required for agricultural purposes instead of timed watering sessions. Furthermore automated systems can indicate faults in water supply, tank leaks, and faults with irrigation systems – letting you know immediately before wastage becomes too serious and expensive.

All of the sensors and devices mentioned can communicate via wireless networks using WiFI or Zigbee-based technology. For remote situations or multiple-site use these WiFi devices can then communicate via the mobile broadband modems and existing cellular networks. Whether you’re in town or abroad, the data can be accessed via the Internet from almost anywhere.

The examples mentioned above may sound like overkill – or replacement of the work of an experienced farmer. However by automating systems and gathering data remotely you can reduce the time required to stay on top of routine tasks, increase efficient use of expensive resources, become immediately aware of any problems – which leaves you with more time to grow your business.

As an Australian organisation led by a team with a diverse background and industry experience, the LX Group can partner with you for your success. With wireless data and bespoke hardware experience in a wide variety of industries we can help you make the most of your business with our expertise and the best technology from around the world. For more information or a confidential discussion about your ideas and how we can help bring them to life – click here to contact us, or telephone 1800 810 124.

Published by LX Pty Ltd for itself and the LX Group of companies, including LX Design House, LX Solutions and LX Consulting, LX Innovations.

Moving on from our examination of Hardware design directions for Internet-of-Thing solutions, we now turn to the software portion of the solution. As there was many hardware options to consider, there is also a variety of choices to select from when looking for a service to collect data from and interact with your hardware. Each have their own features, costs and drawbacks – however these factors and more are subject to the goals of your project.

Nevertheless each have their own distinctive features, so let’s examine three existing and experienced market players in more detail. The first is known as “cosm”, however previously called “pachube”. Cosm is flexible in that you can use your own hardware designs or existing hardware from other vendors, and no hardware licensing is required. You can prototype very easily with cosm using inexpensive development platforms such as NXP’s mbed or even an Arduino-compatible board. This allows your hardware team to get started straight away.

However the service is mainly for capturing and organising “feeds” of data from connected devices, and this can be done for zero cost. There are other options that allow device management and provisioning, however they are in beta stage at the moment. Nevertheless the cosm platform is effective and excellent for capturing data from remote devices for analysis and action – and with very low start-up and running costs it’s great for experimenting or proof-of-concept prototypes.

The next service we consider is “Thingspeak”. This is a fully open-source IoT platform that designed for data feeds and interaction with hardware in both directions. You can also import existing data collected before implementation. Although Thingspeak is open-source, it does provide security via API keys and user authentication. Rules can be created that react when data reaches a certain value or parameter – which cause twitter messages, can trigger hardware or other devices via a connected PC.

You can also export all captured data in .csv file format for ease of local analysis or system transfer. Due to the openness of the system, there’s a great variety of tutorials and examples available for Microsoft .NET, Arduino, python, processing and other environments – which will help your team get up to speed. And currently the service is no-charge. With these factors in mind, Thingspeak can provide a simple solution however more direct enquiries with the organisation would need to be made with relation to long-term changes in costings.

Finally we take a look at “Nimbits”. This service provides the usual cloud-based data gathering, analysis and so on – but using the Google Apps. This offers an incredibly reliable server, integration with Google Docs and other related software tools. As with Thingspeak, Nimbits is fully open-source and allows import and export of your own data. Nimbits offers integration with social media such as facebook and twitter.

The service is free for up to 1000 API calls per day, and then one cent per 1000 calls. Therefore you can again try it for free, or at a very low cost. Getting started is simple, with a range of tutorials on data capture, and interaction or messaging based on circumstances. It does require more coding than cosm or Thingspeak, however this isn’t an insurmountable challenge.

The IoT industry is growing, and even as we write this more services are being introduced and demonstrated. It can be difficult to choose which service to use, as they’re all quite young and untested over the long term, so having hardware and plans that can span two or more different services is essential for the longevity and sustainability of your IoT project.

Here at the LX Group we can discuss and understand your requirements and goals – then help you navigate the various hardware and other options available to help solve your problems. We can create or tailor just about anything from a wireless temperature sensor to a complete Internet-enabled system for you. For more information or a confidential discussion about your ideas and how we can help bring them to life – click here to contact us, or telephone 1800 810 124.

LX is an award-winning electronics design company based in Sydney, Australia. LX services include full turnkey design, electronics, hardware, software and firmware design. LX specialises in embedded systems and wireless technologies design. https://lx-group.com.auPublished by LX Pty Ltd for itself and the LX Group of companies, including LX Design House, LX Solutions and LX Consulting, LX Innovations.