Jump to content
WEC2019 Call for Abstracts Read more... ×

Search the Community

Showing results for tags 'lpwan'.



More search options

  • Search By Tags

    Type tags separated by commas.
  • Search By Author

Content Type


Forums

  • IoT Community Forum
    • IoT Engineering
    • IoT Industry News
    • Community Agenda

Product Groups

  • 10 Things you should know about the IoT

Categories

  • Knowledge Notes
  • Case Studies
  • Announcements

Categories

  • Technology Vendors
  • Consultants
  • Research Organisations
    • Universities
    • Government Agencies

Blogs

  • IoT intellectual property strategy
  • Hook, line and blog
  • Productivity-focused IoT and M2M
  • IoT Thoughts and the Dawn of new Era
  • Making IoT Connectivity Great
  • Microsoft Cloud Workshop: IoT on the Edge
  • Waleed Ahmed

Calendars

  • EA’s IoT Community Activities
  • Other IoT Events
  • Organising Committee Meetings

Find results in...

Find results that contain...


Date Created

  • Start

    End


Last Updated

  • Start

    End


Filter by number of...

Joined

  • Start

    End


Group


Found 16 results

  1. Morteza Shahpari

    A whitepaper on NB-IoT

    Dear all, IEEE Communication Society just published a whitepaper from Anritsu about the NB-IoT. It is entitled "NB-IoT: Characteristics and Considerations for Design and Verification." It can be downloaded from here: https://event.on24.com/wcc/r/1787693/A92FD100BE9027E11FE04351AFF340DB I believe it might be of interest especially for those active on the communications sides of IoT. They don't have a strict sharing policy, so I attach the document here. Kind regards, nbiotwhitepaper1530112129543.pdf
  2. Nadine Cranenburgh

    Building Management Systems

    Introduction The concept of IoT Building Management Systems (BMS) as a service is poised to change the building industry. As the price of internet connected sensors comes down, a large number of sensors can be placed in a building to provide multiple data points connected to advanced cloud based analytical systems. This delivers superior BMS performance to traditional engineering approaches. Building owners own their data, while allowing service providers to help them optimise the efficiency and sustainability of their facilities. This approach also facilitates auditing of the actual performance of building management systems during the critical Defects Liability Period. Traditional vs IoT BMS The purpose of BMS is to achieve sustainable buildings and cities. They should increase efficiency, resilience, security and productivity, as well as reducing environmental impact. They may also incorporate intelligence (as in smart cities) and have the capacity to detect and fix damage. Traditional BMS were pioneered several decades ago. They started the process of automated control and data collection. A diagram of a traditional BMS is shown below. Diagram courtesy of Bob Sharon, Blue IoT Traditional BMS were often proprietary systems. They were expensive to purchase, and modifications to data extraction rules or reporting functions (“steering wheel options”) were also costly. This meant that many BMS owners did not use their systems to their full potential. Other challenges included the long lead times to make changes to the system, the high cost of the cabling to connect extra sensors, specialist programming services required (also costly), and limited alarm complexity without blowing out the budget. Data extraction and report customisation was typically complex and expensive, as was integrating additional data sets from additional systems or devices. And in many cases, the BMS vendor owned the data. A diagram of an IoT BMS is shown below. Diagram courtesy of Bob Sharon, Blue IoT IoT BMS solved many of the issues of traditional BMS systems through open system architectures, wireless technology instead of cabling, increased agility and integration, and reduced operation, modification and maintenance costs. A general comparison between traditional and IoT BMS is shown in the table below. One comment is that some tradition BMS are also starting to become more open. Diagram courtesy of Bob Sharon, Blue IoT Democratisation of data is another advantage IoT BMS have over traditional systems. Open source platforms where the client owns the data allow system modifications to be easily made, and the client to change vendors to meet their service requirements. This trend is set to increase in BMS and other IoT applications. The transition of BMS from traditional to IoT systems is still progressing. So for mission critical applications it may be advisable to use an open source traditional BMS with two-way communications and control form the cloud, with the option to shift to complete cloud operation as the technology matures. Architecture considerations for IoT BMS Considerations when choosing the data aggregation and IoT architecture for an IoT BMS include: Which protocols should connect the sensors and IoT platform? What form of communications technology best suits the application (eg Zigbee, wifi 802.x, Sigfox, Bluetooth low energy (BLE) and LoRaWAN? How will your application engage with the cloud? Who will own the application data (vendor, building owner, users of devices)? Is an open or closed architecture most suitable? It is also recommended that a highly resilient (tier 3 or tier 4) data centre is used for BMS to ensure that data management meets requirements. Sensors and Predictive maintenance One of the problems with traditional BMS is the cost of adding additional sensors, which means that the minimum number is used. With IoT BMS, this cost is greatly reduced, which opens up opportunities for a wide range of data collection to be integrated. It is important to pay attention to data calibration and validation, to ensure that high quality, accurate data is collected. A diagram of some of the sensors which could be used in an IoT BMS is shown below. Diagram courtesy of Bob Sharon, Blue IoT Self-healing and predictive maintenance In particular accelerometers, vibration transmitters and switches can be used to monitor critical rotating machines, and perform predictive maintenance. For example, accelerometers can be used to measure vibration and measure the harmonics of motors. Through monitoring, faults can be fixed before they fail. Advanced machine learning tools will be invaluable for implementing self-healing machines that can dramatically reduce maintenance costs and risks of outages and out of hours maintenance. These cost reductions can offset the cost of installing an IoT BMS. Data analytics There are various data analytics platforms that can take data from thousands of sensors in disparate building management systems (over thousands of buildings if necessary) and create effective interactive analytics and visualisations for end users. This data can be interpreted by engineers and other experts to solve issues that are detected. Security Security of IoT BMS is crucial to ensure that hackers do not take control of the BMS or use it as a pathway to corporate networks, both of which can cause significant damage. A robust, holistic security architecture should be chosen, which implements security at every level including choice and security measures and levels for all of the following components of the BMS: sensor hardware communications protocol cloud IoT platform gateways cloud data centre Other considerations are whether encryption is used, if AI is used to check for unwanted signatures, whether a mesh network being used for sensor communication (can introduce additional risks), which geographic locations the data is going to before it reaches the data centre (and associated risks vs timely transmission of data). While risks cannot be entirely eliminated, they can be greatly reduced with careful security planning and design. An example of how BMS security can be implemented using LoRaWAN is shown below. Diagram courtesy of Bob Sharon, Blue IoT LoRaWAN has the advantage of being able to be encrypted, and the sensors are isolated. The data goes from the sensor directly to the gateway. From the gateway, it goes out over either 3G or 4G, or to another LoRaWAN base station, depending on the system design. This lowers the risk of hacking and additional AI layers can be added for further security. Two-way communication may also be available depending on the class of LoRaWAN used. This example is suitable for low bandwidth data. Sources: The content on this page has been primarily sourced from: Webinar titled “The death of Building Management Systems as we know them” by Bob Sharon, Chief Innovation Officer, Blue IoT See also the article of the same title in our discussion forum with some comments.
  3. until
    Predictive Maintenance Webinar Presented by Microsoft and Happiest Minds LIVE WEBINAR:1/11/2018 AT 10:00 AM PST DURATION:60 MINUTES ABSTRACT: Join us as we discuss Predictive Maintenance for Equipment Manufacturers. During the webinar we will show you how AI and IoT, connected and smart ecosystem can ensure equipment uptime and maintenance schedules using historical data. Register now for the upcoming 60 minute webinar! Learn and Apply: Prevent costly equipment failures. Avoid unscheduled downtime by analyzing streaming data to assess conditions, recognize warning signs, and service your equipment—before it fails. Learn from machine behavior to improve products. Capture and analyze data with machine-learning algorithms and use it to fine-tune processes and make modifications that improve product quality and increase customer satisfaction. Maximize uptime. Increase the efficiency of your fleet and factories by using machine learning to proactively and strategically schedule maintenance when assets aren’t in use. Register Today: http://bit.ly/ IoTinAction-Webinar About Speakers: Sudhama Vemuri Director Business Development, Partnerships & Alliances, HappiestMinds Sudhama is a business development leader in the Internet of Things (IoT) domain. With more than 17 years of experience in sales, new market development, account management in product engineering, smart energy and IoT, Sudhama has varied experience across large organizations like Wipro and NEC as well as IoT start-ups like Altiux Innovations and Cupola. He currently heads the partnerships and alliances for the IoT ecosystem at Happiest Minds. Neal Meldrum Sr. Industry Manager for Manufacturing & Resources Industry, Microsoft Neal is currently working as a Senior Industry Solutions Manager with the WW Discrete Manufacturing Group where he is responsible for Remote Monitoring and Predictive Maintenance scale solutions and industry Pod community management. He brings with him 20 years of experience in the Industrial Automation industry focusing on product development, application engineering, program management and cloud-based remote connectivity solutions. Neal enjoys the hands-on experience of developing and deploying IoT solutions using a variety of Microsoft technologies. Tom O’Reilly General Manager OEM Embedded, Microsoft Tom O’Reilly is a General Manager of the IoT Device Experience team globally at Microsoft. Tom leads the global field marketing and breadth sales teams that work with our IoT ecosystem to help OEM’s, ISV’s, SI’s, Distributors and Aggregators learn about and build devices, services and implement cloud solutions on the Azure platform. His management responsibilities include business development, sales, channels and alliances. Tom has extensive experience in the information technology industry. Prior to joining Microsoft, Tom held a variety of global and regional senior executive positions including sales, marketing, business operations, business transformation and application development within multinational companies such as Amazon Web Services, Dell and Lenovo. Originally from Sydney Australia, Tom has lived and worked in China, Singapore and the US for more than 15 years. CONTACT https://onlinexperiences.com/scripts/Server.nxp?LASCmd=AI:4;F:QS!10100&ShowKey=46586&LangLocaleID=1033&AffiliateData=HMMarketing
  4. Nadine Cranenburgh

    Smart Metering of Utilities

    Introduction Smart metering using IoT has the potential to increase efficient use of utilities and identify and resolve issues in supply infrastructure in the utility industry. One definition of smart metering is the collection of metering data on utility (electricity, water, gas) use, and the systems and processes that derive value from the data. It also enables two-way communications from the meter to utility providers and users, and involves intelligence and processing within the meter that differentiates it from simple automated meter-reading systems that send a reading at specified intervals. Smart metering is widely used in the electrical power industry, due to ready availability of power for IoT devices, however has proved more challenging in metering other utilities such as water. Smart meters enable users and suppliers to gain insights into the utility use of a particular site, piece of equipment, house: anything with a meter. It also gives electricity distribution or water network operators insights into the operation of the network. On the supply end of the meter, utility providers can start to understand what demand is on the network, and when and where there is demand. Smart metering solutions have the following key focus areas: sustainability: reducing the amount of resources that we consume and the energy required to treat or distribute the resource increasing labour efficiency (eg. installing a sensor rather than having a person check manually) increasing economic efficiency As with any IoT project, the cost of smart metering solutions needs to be offset by efficiency or cost savings driven by value extracted from the data collected. One key to increasing efficiency with smart metering is to provide customer friendly data visualisation, interactive analytics and data sharing to allow users to monitor and modify their utility usage. This may not be necessary for corporate users, who will require integration of smart metering data with their own business systems to drive economic and operational benefits. Enrichment of data with additional sources (such as weather and home automation data) also adds value, as does automating processes and work flows by feeding smart metering data or summaries into scheduling, reporting and service systems. Monitoring water use can also businesses predict future utility use for more informed financial planning. Smart metering of water The water industry has historically lacked economically IoT solutions for smart metering. Only around one percent of residential water meters (95% of the water market) are smart enabled. However the application of IoT technologies to high water users is now delivering significant results. Low cost, high volume remote sensing devices are using new low power wide area network (LPWAN) communication technologies and advanced data analytics to develop new business models for the management of water use. Users are more easily able to identify water leaks and consumption trends, to generate insights and facilitate smarter action. The key components of IoT in the water industry are similar to other vertical IoT solutions: · physical layer: low cost, low power remote sensors and devices · network layer: LPWAN, other connectivity · Cloud and edge computing · Data storage, analytics, machine learning · Integration with operational and business systems These components and their relation to each other are shown in the diagram below. Diagram courtesy of Rian Sullings, WaterGroup Pty Ltd Machine learning is used to improve the efficiency data analysis, especially for large data sets for cities rather than individual buildings. Integration of smart water metering systems with operational and business systems is a developing area, as historically they have been stand alone systems rolled out by water utilities with links to billing and some data analytics. Future developments are likely to include data connections to systems that schedule maintenance work, and automatic alerts to operators to resolve detected water leaks. Smart water meters distinguish baseflow (constant, steady flow) from leaks (steady or slightly fluctuating use of water which varies from the norm). Data analysis can inform other efficiencies including timing of air conditioning operation to maximise efficient use of cooling towers. Leak detection provides the greatest economic benefit of smart water metering. A recent project delivered water savings that covered the cost of smart meter installation in less than a year. The diagram below shows the increase in water usage (dark blue line) caused by a leak in the roof sprinklers during the new year’s break at a facility. An automatic alert sent by the smart metering system allowed the leak to be detected and fixed in a matter of days. Diagram courtesy of Rian Sullings, WaterGroup Pty Ltd Challenges Challenges to IoT smart metering solutions can be industry specific. For example, the water industry has infrastructure, such as underground pipes and meters, that are very difficult to access and successfully establish data communications with. This has historically made implementation of IoT and other electronic solutions (end-to-end telematics, SCADA) solutions challenging, as they require deployment of devices with access to power and communications channels. Prototypes are being developed for Sigfox smart metering devices outside North America and Europe, as the frequencies vary between regions, and smart metering devices have not been widely used outside these areas. There is also a limited amount of knowledge of developing smart metering applications for IoT, particularly in the water industry, so collaboration with professional organisations and between developers is important. Another challenge is educating utility users that installing a smart metering system will not increase sustainable resource use unless there are clearly defined goals and methods to store, analyse and feed data into decision making to change behaviour to maximise efficiency. To do this, smart metering systems need to be integrated with business or operational systems, which can be challenging as some utilities (eg. water), currently have limited standards to aid integration of IoT data. Security of smart metering systems is also a concern, particularly for government run systems. This can result in private servers being set up rather than hosting smart metering data in the cloud. Data ownership and privacy are also challenging, particularly for sharing of data collected from private homes. Suppliers and Innovators Australian smart metering company WaterGroup has formed a partnership with IoT communications provider Thinxstra to use the Sigfox LPWAN to allow high water users to detect leaks, and has received an award from the Australian communications industry for positive application of IoT technologies. Over the past few years, South East Water (SEW) in Victoria have been trialling a range of different Internet of Things (IOT) technologies with the goal of creating the most advanced water and waste water network in Australia. The trials are aimed at identifying an IOT platform that will allow the connection of around one million monitoring and controlling devices across SEW’s water and wastewater network using a low power wide area network. More information is contained in the case study page for this project. Standards The Australian national data standard standard for energy smart metering is NEM-12, administered by the Australian Energy Market Operator (AEMO). Standards for IoT-based smart metering of water are still being developed. There is no standard format data storage and transfer, so there are many different file types and formats, which are difficult to integrate. Middleware software can be used to convert data into a common format for integration. Other areas for development in IoT smart water metering data standards include reliability, communications protocols and security. IoT smart metering applications in Australia also use the Hypercat standard for cataloguing and storing IoT data. Sources The content in this page has been primarily sourced from: Webinar titled ‘Smart Metering for Water with the Internet of Things’ by Rian Sullings, Manager Smart Metering & IoT, WaterGroup Pty Ltd Further information Discussion of audience questions from Webinar titled ‘Smart Metering for Water with the Internet of Things’ by Rian Sullings, Manager Smart Metering & IoT, WaterGroup Pty Ltd
  5. World's first NB-IoT based Smart Street Lighting system enabled in the Greek city of Patras serves as a shining example of the infinite potential the Internet of Things can bring to urban areas, as well as the additional benefits of the innovative NB-IoT technology for smart city applications. Deutsche Telekom Group’s subsidiary in Greece, COSMOTE has implemented a Smart City pilot based on Narrowband Internet of Things (NB-IoT) technology in cooperation with the municipality of Patras. The joint project will offer the citizens and visitors of Patras smart parking and smart lighting solutions in selected locations in the city center. The installed Smart Lighting systems, part of the Smart City pilot, will be adjusted to different light intensity levels according to the season and time of the day, reducing electric power consumption by up to 70%. NB‑IoT (LTE Cat NB1) positioning modules and chips from u-blox are enabling the Smart Street Lighting Control system from Flashnet in Romania, inteliLIGHT®. More details from the u-blox Press Release here. The pilot in Patras is not only the first such application in Greece, but also among the first NB-IoT smart city solutions in Europe. In Germany, Deutsche Telekom Group is also working with the cities of Hamburg, Dortmund, Duisburg, and Moers to offer smart parking solutions based on NB-IoT. The NB‑IoT protocol targets IoT applications that have low bandwidth requirements, as such it is ideal for smart lighting. As part of the LTE family of standards, NB‑IoT can be supported within existing LTE infrastructure, offering carrier‑grade reliability and security, as well as excellent penetration and stability. Read more about the Smart City solution full story here.
  6. Australian smart water meter company WaterGroup has signed a five-year partnership with IoT network operator Thinxtra to use IoT to enable large water users to detect water leaks. Full press release: https://www.thinxtra.com/2017/07/watergroup-joins-forces-with-thinxtra/
  7. Ramon Fernandes

    LoRa Vs NB-IoT

    Good article with a point-by-point LoRa vs NB-IoT analysis, read it and try to find which of these LPWAN protocols has more to offer: https://www.linkedin.com/pulse/lora-vs-nb-iot-hussain-fakhruddin
  8. The cellular carriers have been touting two standards for low power wide area networks. LTE-M has higher data rates, consumes more power and is in the middle of rollouts in Europe and the U.S. NB-IoT has a smaller payload and is reportedly cheaper. The idea is that instead of using a technology such as Sigfox or LoRA, a device manufacturer needing a cheaper low power network option would stick with cellular. The reality is proving to be different. Both articles have European operators discussing some of the challenges associated with the cellular LPWAN tech so far. Price, security and interoperability concerns are apparently slowing adoption. Articles: Light Reading, The Register
  9. Discovery Ag and National Narrowband Network Co (NNNCo) have launched a joint venture, Connected Country, designed to provide LoRaWAN for rural areas and announced at last week’s Australian Farm Institute’s Harvesting the Benefits of Digital Agriculture conference in Melbourne. Until now, the widespread use of sensors has been constrained by the cost of transmitting data over existing networks — and the fact significant areas of agricultural land did not have adequate network coverage. https://www.nnnco.com.au/news/commsday-nnnco-forms-jv-discovery-ag-new-nationwide-agriculture-iot-net/
  10. A new low power long range wide area network is now based in ULTIMO, Sydney. Apparently, it is based on Amsterdam's The Things Network. Here is more information: http://www.businessinsider.com.au/the-internet-of-things-has-just-gone-green-2016-7
  11. Tim Kannegieter

    Update on NB-IOT standards

    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
  12. Tim Kannegieter

    Ingenu

    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
  13. Tim Kannegieter

    NNNCo

    NNNCo provides LPWAN Network services in Australia using the LoRaWan protocol. https://www.nnnco.com.au/
  14. Tim Kannegieter

    LoRaWAN

    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
  15. Tim Kannegieter

    Sigfox

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

    Taggle

    A provider of LPWAN technology. The technology has been developed in Australia by a company of the same name. http://www.taggle.com.au/
×