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Tim Kannegieter

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  1. Tim Kannegieter


    "bIoTope (Building an IoT OPen innovation Ecosystem for connected smart objects) is a RIA (Research and Innovation action) project funded by the Horizon 2020 programme, Call ICT30: Internet of Things and Platforms for Connected Smart Objects. bIoTope lays the foundation for open innovation ecosystems, where companies can – with minimal investment – innovate by creating new Systems-of-Systems (SoS) platforms for connected smart objects." CSIRO is involved in this project. Website: http://biotope.cs.hut.fi/
  2. The Internet of Things (IoT) is expected to deliver a tidal wave of data. It has been estimated that 25 gigabytes of data is generated by the average smart car every hour. This will be a major challenge for any operator of fleet of smart cars. In the future, it is conceivable that all cars will be generating this amount of data and there were roughly 18 million vehicles in Australia alone, in 2015. This is just one example in a myriad of potential applications of IoT. One project that is generating more data than almost any other in the world is the Square Kilometer Array. It's an international astronomy project currently being built in Australia and South Africa. High frequency radio telescopes are being installed in South Africa and low and medium frequency radio telescopes are being installed in west Australia. This will be a coordinated system of 3000 radio telescopes with a combined area of one square kilometer. The system is going to be operational by 2020 and the computer infrastructure to handle the amount of data that will be coming from that system does not yet exist. The square km array is expected to generate 30 petabytes of data a day. There is no cloud service that can currently accommodate 30 petabytes of data per day. You may have seen charts which show generation of data from the IoT and production of storage devices, and they're diverging quite significantly. The world is already generating much more data than we can afford to store. Another example of such a large data volumes is Large Hadron Collider, which generates 10 times less data, about three petabytes of data per day, but they can still cannot afford to store it and process offline because they don't have the luxury to store all that data. Sometimes physicists complain they could miss some important revolutionary discoveries simply because they can't afford to store the data. So the world is becoming familiar with dealing with data in terms of petabytes (1015) and spy agencies around the world are reportedly collected data in the realm of Yottabytes (1024). However, experts are now saying that the IoT will force us to think in terms of Brontobytes (1027). To compare, three exabytes (1018) is the amount of data contained in half a million of libraries of the size of US Library of Congress, which is considered the largest library in the world. These large projects and the IoT generally is driving a paradigm shift towards new architectures for data analytics. Source: A presentation by Arkady Zaslasky, Data 61, CSIRO in a presentation titled Harnessing the IoT Data Flood
  3. Tim Kannegieter


    Because the vision for the IoT is to have hundreds of billions of things, each with their own unique ID, addressable on the Internet through URIs or IP addresses. This requires that the majority of things will use the IPv6 protocol, which allows for much larger volumes of IP addresses than the previous IPv4 protocol. A key issue for IoT practitioners is that the IPv6 protocol has not yet be universally implemented and telecom providers are not yet geared up to servicing owners of objects rather than owners of mobile phones.
  4. Tim Kannegieter


    Introduction Many IoT devices can be powered from fixed supply such a mains-derived source, or a vehicle electrical system. However, a key development in IOT has been the reduction in power requirements and technology advances, which has enabled use of batteries to reduce wiring costs to supply power. This is dramatically increasing the range of things that can be monitored and controlled. There are two main classes of batteries used in IOT - primary non-rechargeable batteries or secondary rechargeable batteries. Primary batteries Non-rechargeable batteries that are designed to last for 10 or 15 years are expensive, in the order of AU$10 or AU$20 for AA cells or a C Cell. Example technologies are a LiPolymer and LiFe. LiFe batteries perform quite well in much greater thermal extremes. Secondary batteries Rechargeable batteries are often used in remote applications, typically solar powered. The main rechargeable battery technology is Lithium polymer and Lithium Ion. Lithium battery technology has encountered problems in some high power applications, where malfunctions of other kinds of products have made the news. However, the main issue for IoT has been in the supply of such batteries because Lithium batteries over a certain size have been banned from air freight. This can impact on the manufacture and maintenance of IoT devices. A safer alternative to Lithium polymer with a longer cycle life and constant discharge voltage are lithium iron phosphate (LiFePO4) cells. Engineering challenges: Lithium polymer which make up the bulk of rechargeable batteries, such as those found in supermarkets, technology, are very cheap, in the order of a few dollars. However, batteries of the same technology designed to last 10 or 20 years can cost $20 to $30. The choice of a battery technology which suits the environment is important. In designing IoT systems, a trade-off exists between battery cost and the cost of more frequent battery replacement. In applications where it is difficult to access the device, or the labor cost of changing the batter is prohibitive, a good quality primary battery makes sense. Where devices are visited regularly for other purposes, a cheaper rechargeable battery technology may be more appropriate. One particular challenge for IoT applications is in outdoor environments exposed to direct sunlight. The inside of device enclosures can get very hot in such circumstances, in the order of 70 degrees Celsius. Using the batteries during these conditions can significantly degrade their performance and life expectancy. This needs to be taken into account when designing the system and the enclosure. In some applications, it is possible that a battery is not needed at all and energy harvesting options can be explored many of which use alternatives such as super capacitors.
  5. Introduction Energy harvesting, also known as power scavenging, is the term used to describe methods for powering IoT devices from its local environment, rather than by mains power or primary batteries. The main sources of environmental power are photovoltaic, thermoelectric, kinetic, and radio frequency. These are complement by energy harvesting and power storage systems. A key misconception is that people equate power scavenging with perpetual life, that device will run forever. However, all systems have limitations. For example, a rechargeable cell powered by a solar panel will die after a period of time or a set number of cycles. So the intelligent design of energy harvesting systems is important, and this may or may not include a battery. Kinetic Kinetic energy harvesting systems are powered by physical motion. Available wherever thing are moving. Examples range from sources of micro-power, such as switches/buttons and watches/wearables through to larger sources such as wind and water. The micro-sources produce a small spike of energy that is just enough to send a small piece of information. The larger sources do not have to be traditional wind power or hydroelectric systems. From an IOT perspective, it is possible to create miniature devices that fit inside pipes to power a single device. It is possible to fit energy harvesting devices inside pipes with moving water to power an IOT device measuring the flow in remote locations. Thermoelectric Thermoelectric energy harvesting systems are powered by differences in temperature, usually between a source at a higher or lower temperature and the ambient environment. Thermoelectric sources are often available in industrial settings which often have, for example, cold or hot pipes. There are even products that can generate power from the difference between skin temperature and the surrounding air, to power a wearable device. Solar Solar, also known as optical energy, has been used for a long time has been used in many different applications because the power density that can be generated from a solar cell is reasonable significant for its size. The main challenge with optical energy is to model how big a solar panel, and associated power storage system, needs to be to make sure that an IoT system will function through natural variations in light levels and in the worst case scenario. Radio Frequencies RF energy harvesting system, and the closely related induction charging, can extract energy from radio waves, in the same way that old crystal set radios extracted enough energy from AM broadcasts to listen to them without a batter. However, this approach has the lowest efficiency of all the harvesting techniques because the amount of power that must be broadcast in order to get a tiny little bit of power exchange over even a small distance is huge. The most useful example of this technique is the use of passive RFID tags, which normally consist of a tiny chip and very thin antenna. As the RFID tag passes through a gate or scanner, there is a wireless power exchange that's very short range. The main reason RFID tags can be manufactured for few cents and last such a long time is because have no battery. Engineering challenges The main engineering challenge is knowing when it is appropriate to use energy harvesting. There are a small number of applications where energy harvesting just makes sense, such as switches and some solar cells on devices that are visited regularly. However, many people fall into the trap of including energy harvesting in their IoT design because they can, when it fact it might not make sense to use it. For example, a kinetically charged dog tracking collar is possible but a battery may much more cost effective. Possible applications where energy harvesting does make sense are: Unusual form factors –e,g, where you've got to get something really thin, woven into clothing etc. Massive deployment applications – e.g. where it's not commercially feasible to replace or recharge batteries. Inconvenient locations – e.g. places that are really difficult to get to. Power storage Power storage option range from batteries through super-capacitors to solid-state options. The main factors to consider are cycle life, before the component needs to be replaced, the rate at which it goes flat, the overall storage capacity and the length of time the charge is available to execute the IoT device’s function. A comparison of common power storage options. Diagram curtesy of Simon Blyth, LX Group. High density rechargeable battery technologies generally have a self-discharge problem and can be hard to charge up using the small sources of power available via some sources of energy harvesting. Super capacities obviously only hold their charge for a very short time but provide an alternative in the right contexts, particularly where the device is being charged/discharged frequently. Examples may be on rotating equipment etc. Energy harvesting chips Many manufacturers are now making chip-based solutions that make it easier to design an energy harvesting system into an IoT device. Comparison of a range of chip-based energy harvesting systems. Diagram curtesy of Simon Blyth, LX Group. Selection of the right energy harvesting chip would relate to the overall architecture and design of the IoT device. Technology companies Key suppliers of energy harvesting technologies include: Micropelt Laird PowerFilm IXYS Kinetron Volture WiTricity IDT Cota Powercast muRata Panasonic Maxwell Cymbet Infinite Power Solutions Sources: Information on this page was primarily sourced from the following: A webinar titled Power Scavenging in IoT Design by Simon Blyth, CEO, LX Group
  6. See apprenticeship program Siemens is offering in Melbourne. 20 Places. https://www.seek.com.au/job/32616578?savedSearchID=13153406&tracking=JMC-SAU-eDM-JobMail4.01-3881
  7. There are a range of factors or approaches that can be used to secure communication to IOT devices: Virtual Private Networks: VPNs are good as long as both points of the connection are secured. However, if one end of the VPN is compromised, then a hacker has access to the entire stream of information. If both the source and destination points of the VPN are both solid and secure, then the VPN is a fantastic way of transferring traffic in IOT. SSL could be used, even all the way through encrypting the data before it's sent and received, attributing hash back values to the data prior to it being sent and then decoding it on your end.
  8. There are some "IoT routers" being delivered by vendors such as Dell and other industry players who are doing deep packet inspection style firewalls for industrial protocols such as modpus tcp, Ethernet/IP, etc. A Google search for IOT routers will show vendors are actually trying to get into this space. However, deep packet inspection can come with a significant processing overhead. Good capacity planning would be required when looking at this approach.
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    Cisco Virtual hackathon for Asia-Pacific. Registrations are now open and runs to 19 Feb Cisco will offer a total prize pool of 25k and one grand winner gets $15K! Participants will: -Get access to Cisco technologies -Be coached and trained by Cisco experts -Get assistance at a Cisco innovation center in Sydney or Perth http://bit.ly/cisco-virtual-hackathon
  10. Tim Kannegieter

    UXC Saltbush

    Australian owned, ICT security consultancy company Website: http://www.saltbushgroup.com/
  11. Tim Kannegieter


    Shodan a search engine specifically designed for the Internet of things. It allows the user to find specific types of things connected to the internet using a variety of filters. This is enabled by storing the meta-data that the IoT devices broadcast. Shodan allows user to determine all parts of your network that are accessible from the internet, categorise the things into types, show what devices are broadcasting using particular SCADA protocols (such as Modbus, S7, DNP2, Fox, BACnet, Ethernet/IP, GE-SRTP, HART and PCWorx) and show where they are being used geographically. Website: https://www.shodan.io/
  12. Tim Kannegieter

    Spiral Systems

    "Spiral Systems conceive, design, build, test and introduce into service systems that meet customer needs, comply with safety and security regulations and are highly maintainable." Website: http://www.spiralsystems.com.au/
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    View the recording: This webinar has passed. Members of Engineers Australia can view the recording free on MyPortal. Simply logon and navigate to Industry Applications > Smart Cities ____________________________________________________________________________________________________ Presenter: Dr Paul Neumeyer, Program Manager - Technology and Infrastructure, Sense-T, University of Tasmania What you will learn: · Outcomes and lessons learnt from practical Internet of Things (IOT) initiatives across a range of industries · How to work with data and its infinite applications, combined with sensing technologies and analytics to help see alignments and opportunities · A state-wide approach to collaboration around IOT Description: What can happen when a university, government, national research body and leading businesses collaborate to create a cohesive state-wide strategy to take advantage of and apply the latest digital technologies? The answer is digital transformation across a range of industries. This is exactly what is happening in Tasmania, where a project called Sense-T is driving innovation in agriculture, aquaculture, tourism, health, logistics and natural capital. Sense-T is a partnership between the University of Tasmania, CSIRO and the Tasmanian Government. It has developed a spatio-temporal Data Platform allowing near real-time data to be processed and combined, to help make informed production and operational decisions based on the location and context for their specific needs. With more than 30,000 data streams available on the platform and over ten organisations currently contributing, using and sharing the data, Sense-T has created a unique ecosystem. The presentation will cover some of the outcomes, as well as key lessons learnt, from Sense-T projects that applied IoT and sensing technology to address practical problems. The presentation will also cover the new LoRaWAN initiative in Tasmania and opportunities that it presents for Smart Cities, Smart Communities and a Smart Island. About the presenter: Dr Paul Neumeyer is the Program Manager - Technology and Infrastructure at Sense-T at the University of Tasmania, and is responsible for delivering innovative technology and key infrastructure. Paul is a seasoned technology leader with a commercial track record involving innovation in complex environments. Originally from Hobart, Paul is experienced in commercialisation and established and operated several companies in Sydney. He has wide experience and skills in systems architecture, leading technical teams and has consulted to top tier enterprises. Paul has an engineering background and holds a PhD in Computer Systems Engineering.
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    View the recording: This webinar has passed. Members of Engineers Australia can view the recording free on MyPortal. Simply logon and navigate to Overview > Industry and Standards Title: IOT Testbeds – not the springy kind Presenter: Stephen J Mellor, Chief Technical Officer, IIC What you will learn: What the Industrial Internet Consortium does, how it is affecting the IOT industry and how it can help you Standards and their relevance, including in vertical markets How to set up or participate in IOT testbeds Description: In order to realise the full benefits of the Internet of Things, particularly in industrial settings, there needs to be common protocols to facilitate interoperability and drive the adoption of new business models. One organisation leading efforts globally in this area is the Industrial Internet Consortium. It is a member-driven not-for-profit focused on creating testbeds to test out new technologies. An IIC testbed is a controlled experimentation platform in real world conditions, testing technologies being used in different ways and to discover new business models. Results from testbeds include best practices and requirements for standards, not the standards themselves. This presentation outlines how the IIC works and recent achievements. About the presenter: Stephen Mellor is the Chief Technical Officer for the Industrial Internet Consortium, where he directs the standards requirements and technology and security priorities for the Industrial Internet. In that role, he coordinates the activities of the several engineering, architecture, security and testbed working groups and teams. He is a well-known technology consultant on methods for the construction of real-time and embedded systems, a signatory to the Agile Manifesto, and one-time adjunct professor at the Australian National University in Canberra, ACT, Australia. Stephen is the author of Structured Development for Real-Time Systems, Object Lifecycles, Executable UML, and MDA Distilled. When: 12 midday AEST (Sydney) on 31 January 2017. The presentation will last 30 minutes, followed by question time. Where: The presentation is by webinar. After registering you will be sent details of how to logon. Cost: This presentation is free to members of Engineers Australia (EA), the Australian Computer Society (ACS), the Institution of Engineering and Technology (IET) and IEEE. Just provide your membership number during registration for the event. The cost for non-members is $30. How to register: Please register on the Engineers Australia event system. Note, to register you need to have a free EA ID which you can get on the first screen of the registration page. Take note of your ID number for future events.
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    See http://www.iiotsummit.com.au/
  16. Introduction The mining and energy (oil and gas) industries cover a complex web of operators and suppliers which must work together to deliver commercial outcomes. Drilling platforms and major mines have been early adopters of control technologies, being highly sensored - albeit connected primarily via wired systems. Early efforts focused on major productivity improvements, such as having communication links transmitting the data to a headquarters, allowing a higher percentage of the workforce to work from cities rather than on site. However, periodic downturns in the industry require ever increasing efficiency improvements and IoT has the potential to deliver on that through smaller incremental improvements. Coupled with the global factors driving the IoT revolution, mining and energy are industries ripe for the application of IoT. Because Australia is a world leader in these sectors, it is considered there is an opportunity to also lead the world in the application of certain areas of IoT e.g. data analytics for mining. Application areas The major areas of opportunity for IoT in mining and energy are monitoring and optimization, safety systems, geological systems, site-wide operating systems, and automation. Monitoring and optimization covers condition monitoring of mobile equipment and fixed plants. It covers communication systems, platforms for condition monitoring, data re-purposing and predictive analytics resides. Safety systems include connected wearable technologies, monitoring employees in real time with personnel tracking with location mapping, even seeing what they can see, Site-wide operating systems include automated equipment (such as drill rigs, trucks and lab robots), automated plant operating autonomously to optimise operations, condition monitoring, site surveillance. Site wide system involved integration of a wide range of platforms as no one provider in the ecosystem has the entire holistic solution. In fact the industry is characterised by many providers with solutions specific to parts of the ecosystem. Interoperability and data re-purposings is critical to optimal operation of the ecosystem. Geological sensing is well established in oil and gas, and increasingly applied in mining. It’s taking geological measurements from the rock during real-time operations, working with the data, transmitting it to surface and back to headquarters for interpretation. Data specifically about the same rock comes from different measurements at different times in the project, e.g.e including gravity and magnetic geophysics work done up front, potentially some magnetotellurics a few months later and then actual drilling data. The resolution of the site view is developed and interpreted over time. There is a huge volume of data (the average seismic exploration generates petabytes of data) and analytical/visualisation techniques being matured in IoT systems will play a role to advance this field. Environmental systems for monitoring changes to the environment. Some mines are starting to use drones to replace traditional environmental surveying techniques. Drones can collect lot of visual information within a short space of time and have it analysed by advanced cloud based systems. This can be used to monitor wildlife and flora. Most mines have an over-arching environmental plan to rehabilitate the land as it originally was so you don’t want any introduced species of flora being introduced so you need to monitor population and target areas to ensure you're managing the environment properly. Environmental systems are also employed in a range of associated operations such as dredging and stockpile management, with dust sensors, temperature sensors, water flow sensors, pulling all the data into simple display and management system. Increasingly this kind of data is being displayed on live Web feeds, so the general public can see what’s going on with their environment, what the impact of operations are on the local environment. Specific technologies of interest in mining and energy include: Sensors: Advances in sensing technology will be a driver of efficiencies. For example, sensing technologies are being developed that can be placed directly behind a drill bit to analyse rock in real time rather than waiting for lab tests. Another area of opportunity lies in stockpile management, where better sensing of ore grades will help decide what to put through the mill and when to process it. Drones: Because of the geographically dispersed nature of mining and engergy industries, operators are investing heavily in drones. A drone and single pilot can complete the same work loads of an eight-man environmental study team. Challenges include battery life versus weight and line of sight regulations, which restricts what operations can be done around areas such as railway line inspections etc. There is also a problem with raptors attacking drones which they view as prey. Autonomous vehicles: The mining industry was an early adopter of autonomous vehicles. There is, approximately, a worldwide population of 100,000 mining trucks, compared to over a billion road vehicles. With automotive companies in a global race to introduce self driving cars, the mainstream technology will quickly surpass the early mining technology. For example, suspension technology that adapts to potholes and inconsistencies in the roads would be very useful on mining trucks, which typically costs around half a million dollars every time a tire blows. Key issues Interoperability: Because there are so many niche suppliers in mining and energy, there is a challenge around interoperability between platforms and systems. There is an argument that these industries should leverage standards developed in other industries, such as Industrie 4.0 (See manufacturing). An aspect of this is the need for modularity in the development of software systems. Such systems are developing so fast that it hard to predict what the final deliverable will be. Modularity in systems allows flexibility. Repurposing of data: A large percentage of data collected in mining and energy is not used. However, if that data is accessible to other systems, there is potential for suppliers to come up with new idea of how to utilize that data - to squeeze more value from it. Cultural bias: The mining and energy sectors have traditionally been very insular, with an attitude of going it alone with development of technologies. However, with the rapid pace of development in IoT, this culture means the industry may not take advantage of the latest technologies and begin to lag behind in productivity. Links: IoT MER: The Internet of Things Cluster for Mining and Energy Resources. Sources The information on this page was primarily sourced from the following: A webinar titled Tipping points in mining and petroleum: A perfect storm of convergency creating opportunity through the Internet of things by Steven Travers, Executive Manager – IoT Cluster for Mining & Energy Resources
  17. Tim Kannegieter

    LX Group

    LX Group specialises in IoT and M2M product development. Website: https://lx-group.com.au/
  18. Introduction The main focus of power management in IoT is how to design a low power field device. In the past, the main components of any internet connected device were all power hungry, making operation by battery not practical. These include the microcontroller, sensors, connectivity interfaces and actuation. However, major advances in technology have reached a tipping point where devices operating on batteries for long periods of time (measured in years) is now feasible. This has been accompanied by a corresponding miniaturisation. The electronics in IoT devices can now be dwarfed by the size of the battery. Power management is important because it determines how long a battery powered device can last in a field, and often how expensive it might be. The embedded electronics might cost less than a dollar but the battery and subsections involved in the powering device, could be $30. Thus power is becoming a big limiting factor for how low we can go in terms of cost, size and longevity. Simply, it is more challenging to store energy than it is to pack transistors onto something, so the less power a device needs the less needs to be expended on storage systems. Key engineering challenges: A first step in power management is technology selection, in terms of the major components of the device (e.g.sensor, wireless interface, microcontroller, antenna etc). This can involve searching for and finding low power versions of each component which will still deliver the functionality required. The second step is to ensure that the system is designed intelligently, to minimise power consumption. For example, the system may be designed to take a reading daily or every few seconds. Some design have systems in active mode, taking measurements etc, far more often than necessary. The design should ensure that the devices electronics are sleeping for as much time as possible while still achieving the performance requirements. It can be woken to take the measurement and then put back to sleep. The total energy consumed by a device relates to how frequently a device is in active mode. Diagram curtesy of Simon Blyth, LX Group. The above diagram represents how power is being consumed when particular subsections are on. Some sections will be much power hungrier than others. For example, transmitting on a LoRA or Sigfox link will take much more energy going to be a much larger lack of energy than reading a small temperature sensor or accelerometer. In addition to the height of the power spikes above (amount of power drawn) there is also the width, or the amount of time that the subsection is on. With LPWAN technologies you can often select a bit rate, or how fast you actually communicate. Choosing a lower bit rate may often get you longer range in terms of RF performance. However, it comes at the cost of transmitting for longer. You are consuming more power because that impulse is longer. Another factor that, at a hardware layer, needs to be managed is drainage in sleep mode. Most components on an IOT device will have a lower power mode, which have a very low sleep current of just a few microamps. It is standard practice to design your system to put them into sleep mode when they are not being used. However, individually they all add up and can become a drain on power, particularly when the device has a lot of sensors taking different measurements. One technique to address this is to have real time clock, often within the processor, controlling a power rail. This can be used to completely disconnect all of the components from the battery. The only component drawing power then is the clock or the processor containing it, which periodically wakes up the rest of the system as required. One exception to this rule is when you can make use of a sensor to intelligently minimise the number of times you need to power the system up. Using rules which determine under what conditions it is worthwhile sending information, a sensor can be used to detect that condition and wake the system up. In this context, it may be worth keeping the sensor power up all the time. For example, in tracking applications an accelerometer can be used to determine if the item is actually moving or not. When moving the frequency of reporting may be every few minutes or hours. However, if it then it goes on a shelf and the sensor can tell it is not moving, the system can reduce the reporting to once or day or only to resume when it starts moving again. This is just one example of intelligent design of IoT devices to minimise power consumption and cost. Each application is unique and requires it own strategy to optimise the system. Another factor that needs to be considered in power management is whether to use high quality primary batteries (or mains) as the source of power or to make use of local sources of energy, including sun, heat, movement and ambient RF. This latter approach is known as energy harvesting and may be appropriate if the environment can provide enough energy and the IoT application can be designed with low enough power requirements. However, it should be borne in mind that energy scavenging systems actually have less life in the field than if you go with a primary source. This is because rechargeable batteries (e.g. lithium polymer, LIFE, sealed lead acid battery) reach the end of their life far quicker (often a few years) than high quality primary batteries (such as lithium manganese) that can be designed to last for 10 to 15 years. Calculating current draw To determine the capacity of the battery or requirements of the energy harvesting system, it is important to calculate accurately the expected current draw for a particular hardware design. This is important because it help’s determine how long a particular power cell can power a system. Designers need to calculate this using information from the component data sheets. This needs to be adjusted to what mode the device is operating that device in. This is done for each of the use cases for each subsection. Where the data is not known or clear, the worst case scenario is used. One important use case is when all of the subsystems are lit up simultaneously, which can be used to calculate the maximum the instantaneous current required. It is also important to take into account thermal effects. E.g. a battery data sheet might say it has 890 million amp hours. The different modes it is operated in and the environmental conditions will impact the actual effective capacity of the battery. A safety margin is then normally added and this will depend on the application and the impact of a battery going flat. This approach can be used to determine the overall batter capacity required to power a system and the predict its life expectancy. A good link on calculating IoT battery life is here. Sources: Material on this page has primarily been sourced from the following: Presentation on Power scavenging in IoT Design by Simon Blyth, LX Group
  19. The 3rd Generation Partnership Project responsible for developing 5G mobile broadband standards and the associated NB-IOT technology have announced its Release 13 with Release 14 due June 2017. A presentation provides updates on what these will provide in terms of LPWAN features. See http://www.3gpp.org/news-events/3gpp-news/1805-iot_r14
  20. Tim Kannegieter


    Narrowband IOT (NB-IOT) is a LPWAN technology that is expected to be part of the 5G mobile networks being rolled out by most of the major Telecom operators. The standards for LPWAN have been developed by the 3rd Generation Partnership Project which is responsible for 5G standards.
  21. Tim Kannegieter


    Ingenu is a LPWAN system using Random Phase Multiple Access (RPMA) technology. http://www.ingenu.com/ It has been reported that Ingenu networks are provided in Australia by IOTOz
  22. Tim Kannegieter


    NNNCo provides LPWAN Network services in Australia using the LoRaWan protocol. https://www.nnnco.com.au/
  23. Airlora Communications is a network provider for LPWAN using the LoRaWAN protocol.
  24. Tim Kannegieter


    LoRaWAN is an open global standard for low power WAN connectivity. LoRa is a registered trademark of Semtech corporation, which is a chip company using chirp spread spectrum modulation. LoRa is the term used to describe the physical layout and LoRaWAN is the name given to the MAC layer protocol. LoRA operates in unlicensed spectrum. The exact frequencies vary by region, and the channel plan standard for Australia was released in 2016 by the LoRa Alliance following the release of standards for the EU, USA, and China. One of the more unique features of LoRa is that it can adjust the data rate depending on the path or distance between the base station and the node. This is important because it allows optimization of energy usage. Being a spread spectrum technology the data rate is adjusted by means of modifying the spreading factor of the modulation. The way spread spectrum works is that each bit or symbol is transmitted as a sequence of chirps (or chips), which spreads the signal over a wide channel bandwidth. The spreading factor determines how many chirps are sent for each symbol, which is why the spreading factor affects power. The more chirps that are sent, the more the coding gain, which helps the receiver recover the signal even from well below the noise floor. LoRa is capable of reconstructing a signal 19.5 db below the noise floor, which is why it can transmit at such long a range with low power. The chirps are actually burst of signal with rising or falling frequency (analogous to a bird chirping). Chirp spread spectrum is claimed to be resistant against broadband and narrow-band disturbances and multipath fading, which are important. LoRa networks have been demonstrated to work in a coastal environment across a 15km range using a 100 milliwatt transmitter with only directional transmit receiver antennas. In an urban environment the range is more typically 4.5km. The spreading factor affects time on air and the time the transmitter is turned on to send a packet, so the energy used depends on which channel bandwidth and spreading factor is used. The transmission energy that's in, say, an 11 byte packet, can vary from a few millijoules to a couple hundred millijoules per packet transmitted. Once this is known it is possible to work out how many transmissions you can get out of a battery, taking into account other electronics on the device. Typically this would be in on the order of 10 to 20 thousand transmissions out of a typical cellular phone-type battery. The maximum packet length for LoRAWAN depends on a number of factors and can be up to 256 bytes. However, communications can be broken up into multiple packets which can then be hopped across different frequencies that allow them to comply with dwell time requirements in different regions e.g. using HCMA or FCCs rules which are is slightly different. Typical applications would only transmit approximately 11 bytes which is usually enough to transmit the kind of information being generated by IoT devices. LoRaWAN is symetrical and configurable meaning it can have transmit only, or transmit with an acknowledgement, or you can have bidirectional communication. There are three classes of protocol - A, B, and C. Class A allows asynchronous at any time. Class B transmits on a schedule. Class C is always listening. The listening windows in class A and B are open depending on what the transmitter decides it needs to do. There's a possibility of building different classes of servers. You can also choose to send an acknowledge packet or not, and then you can choose to do what you want to do depending on whether you get that acknowledge. For example, you might transmit, wait for an acknowledge for a period of time. If you don't get it, you transmit again, and you can do that any number of times. You can choose to configure the server to respond in ways that are appropriate for the application. Sources: The information on this paged is sourced primarily from the following: A webinar titled LPWAN: The missing link in IoT by Justin Spangaro, Founder and CEO Airlora Communications Links The Lora Alliance is at https://www.lora-alliance.org/ Because LoRaWAN is open there are several providers of network services in Australia and some large government departments and private companies are implementing their own networks. LoRaWAN network providers include: Airlora Communications NNNCo
  25. Tim Kannegieter


    Sigfox is a French company with a global LPWAN roll out. In Australia, Sigfox is being rolled out by Thinxtra. https://www.sigfox.com/
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