Intelligent Internet of Things (IIoT): System Architectures and Communica...Raghu Nandy
Internet of Things (IoT) can be designed by various approaches with optimistic technology choices. This paper focuses on comparing recent studies on architectural choices and communication approaches for IoT Systems. Understanding Goals of an IoT system and inventing a general prototype for general IoT solutions is uniquely challenging. Existing research prototypes provide us information about IoT systems and their challenges. Existing architectures and communication approaches such as such as Service Oriented Architecture (SOA), Instant Messaging (XMPP) and Web-Sockets Service can be used to develop a general IoT System prototype. SOA provides centralized/decentralized IoT systems. Instant Message services such as XMPP can be used to build distributed and secure IoT platforms. Web-sockets also used to build scalable IoT systems. Overall the choice depends on IoT system Goal and limitations. Intelligent IoT (IIoT) Systems can be seen as decision making system. IoT systems can be built on Cloud infrastructures With Sensor Event as a Service (SEaaS) - Cloud Sensor networks can enable applications to access on-demand real-time sensor data. A generic IoT platform can be built and extended to newer applications and platforms.
Internet of Things requires communication to devices that are either actuators or sensors. Each actuator and sensor has an identity. Each actuator and sensor may be either directly connected to the world wide web or indirectly connected via a type of gateway.
Communication to these devices needs to be reliable. Therefore each device may implement their most suitable communication protocol.
This deck describes the main common protocols and their usage for the Internet of Things
Charles Gibbons
apicrazy.com
Intelligent Internet of Things (IIoT): System Architectures and Communica...Raghu Nandy
Internet of Things (IoT) can be designed by various approaches with optimistic technology choices. This paper focuses on comparing recent studies on architectural choices and communication approaches for IoT Systems. Understanding Goals of an IoT system and inventing a general prototype for general IoT solutions is uniquely challenging. Existing research prototypes provide us information about IoT systems and their challenges. Existing architectures and communication approaches such as such as Service Oriented Architecture (SOA), Instant Messaging (XMPP) and Web-Sockets Service can be used to develop a general IoT System prototype. SOA provides centralized/decentralized IoT systems. Instant Message services such as XMPP can be used to build distributed and secure IoT platforms. Web-sockets also used to build scalable IoT systems. Overall the choice depends on IoT system Goal and limitations. Intelligent IoT (IIoT) Systems can be seen as decision making system. IoT systems can be built on Cloud infrastructures With Sensor Event as a Service (SEaaS) - Cloud Sensor networks can enable applications to access on-demand real-time sensor data. A generic IoT platform can be built and extended to newer applications and platforms.
Internet of Things requires communication to devices that are either actuators or sensors. Each actuator and sensor has an identity. Each actuator and sensor may be either directly connected to the world wide web or indirectly connected via a type of gateway.
Communication to these devices needs to be reliable. Therefore each device may implement their most suitable communication protocol.
This deck describes the main common protocols and their usage for the Internet of Things
Charles Gibbons
apicrazy.com
Utilizing distributed storage administrations, clients can store their Information in the cloud to maintain a strategic distance from
the consumption of neighborhood information stockpiling support. To guarantee the uprightness of the information put away in
the Cloud, numerous information, honesty examining plans have been proposed. A client needs to Utilize his private key to
produce the information authenticators for Understanding the information respectability reviewing. In this way, the client needs to
have an equipment token to store his private Key and retain a secret phrase to enact this private key. In the event that this
Equipment token is lost or this secret phrase is overlooked, the majority of the Current information, trustworthiness inspecting
plans would be notable work. We propose another worldview Called information uprightness inspecting without private key
stockpiling and Plan such a plan. In this plan, we use biometric informationas the client's fluffy private key to Abstain from
utilizing the equipment token. In the interim, the plan can at present Successfully complete the information respectability
auditing. We use a direct Sketch with coding and blunder revision procedures to affirm The personality of the client. We use
another mark Conspire which supports blacklist certainty. The security evidence and the Execution examination demonstrates that our proposed plan accomplishes Attractive security andeffectiveness.
DNA computing based stream cipher for internet of things using MQTT protocol IJECEIAES
Internet of Things (IoT) is a rapidly developing technology that enables “devices” to communicate and share information amongst them without human control. The devices have the features of internet connectivity and networking. Due to the increasing demands of a secure environment in IoT application, security has become a crucial aspect on which researchers have been increasingly focused. Connecting devices to the internet can facilitate intruders to attack devices as they can access the data from anywhere in the globe. In this work, an encryption–decryption process-based stream cipher has been used. The messages between IoT nodes were encrypted using One Time Pad (OTP) and DNA computing. Furthermore, the required key sequence was generated using a linear feedback shift register (LFSR) as a pseudo number key generator. This key sequence was combined to generate a unique key for each message. The algorithm was implemented using source python and tested on a Raspberry pi under Linux open operation system.
Internet Of Things(IoT) is emerging technology in future world.The term IoT comprises of Cloud computing, Data mining,
Big data analytics, hardware board. The Security and Interoperability is a main factor that influences the IoT Enegy
consumption is also main fator for IoT application designing.The various protocols such as MQTT,AMQP,XMPP are used in
IoT.This paper analysis the various protocols used in Internet of Things.
Data Modelling and Knowledge Engineering for the Internet of ThingsCory Andrew Henson
Tutorial on Data Modelling and Knowledge Engineering for the Internet of Things, presented at EKAW 2012, Galway City, Ireland, October 8-12, 2012
http://knoesis.org/iot-tutorial-ekaw2012/
Internet of Things (IoT) plays a vital role in our
day to day life and normally used in our houses, in industry,
schools and in hospitals which implemented outside to manage
and control for taking report the changes in location prevent
from dangers and many more favorable things. Moreover all
other advantages can approach of big risks of privacy loss and
security issues. To protect the IoT devices, so many research
works have been measure to find those problems and locate a
best way to eradicate those risks or at least to reduce their effect
on the security and privacy requirement. Formation the concept
of device to device (D2D) communication technology, IoT plays
the information transfer from one end to another end as node of
interconnection. This paper examines the constraints and
security challenges posed by IoT connected devices and the
ability to connect, communicate with, and remotely manage an
incalculable number of networked, automated devices via the
Internet is becoming pervasive.
Ensemble of Probabilistic Learning Networks for IoT Edge Intrusion Detection IJCNCJournal
This paper proposes an intelligent and compact machine learning model for IoT intrusion detection using an ensemble of semi-parametric models with Ada boost. The proposed model provides an adequate realtime intrusion detection at an affordable computational complexity suitable for the IoT edge networks. The proposed model is evaluated against other comparable models using the benchmark data on IoT-IDS and shows comparable performance with reduced computations as required.
A novel architecture for lightweight block cipher, piccoloeSAT Journals
Abstract Security and privacy are going to be the key factors for the deployment of new applications, since people will only accept these deployments if these are based on secure, trustworthy and privacy-preserving infra-structures. Cryptography plays a major role in the security of data transmission and the development of computing technology imposes stronger requirements on the cryptography schemes. Lightweight cryptography is a cryptographic algorithm or protocol tailored for implementation in constrained environments including RFID tags, sensors, contactless smart cards, health-care devices and so on. These devices are leading to an ever increasing need to provide security. In order to satisfy these needs, secure and efficient encryption and authentication schemes have to be developed. Symmetric-key algorithms, especially lightweight block ciphers, play an important role to provide security in these applications. Piccolo is a new lightweight block cipher which is optimized for extremely constrained devices. Piccolo supports 64-bit block with 80 or 128-bit keys, and has an iterative structure which is a variant of a generalized Feistel network. Piccolo achieves both high security and extremely compact implementation unlike the other Feistel-type structure based lightweight block ciphers. The proposed system deals with an efficient implementation of Piccolo block cipher architecture that will fulfill mandatory requirements such as throughput and speed for low-resource devices like RFID tags and wireless sensors. The new architecture is designed such that it shares the key scheduling block for two plain text blocks concurrently. Key Words: Lightweight Cryptography, RFID, Piccolo, and Fiestel Networks.
Utilizing distributed storage administrations, clients can store their Information in the cloud to maintain a strategic distance from
the consumption of neighborhood information stockpiling support. To guarantee the uprightness of the information put away in
the Cloud, numerous information, honesty examining plans have been proposed. A client needs to Utilize his private key to
produce the information authenticators for Understanding the information respectability reviewing. In this way, the client needs to
have an equipment token to store his private Key and retain a secret phrase to enact this private key. In the event that this
Equipment token is lost or this secret phrase is overlooked, the majority of the Current information, trustworthiness inspecting
plans would be notable work. We propose another worldview Called information uprightness inspecting without private key
stockpiling and Plan such a plan. In this plan, we use biometric informationas the client's fluffy private key to Abstain from
utilizing the equipment token. In the interim, the plan can at present Successfully complete the information respectability
auditing. We use a direct Sketch with coding and blunder revision procedures to affirm The personality of the client. We use
another mark Conspire which supports blacklist certainty. The security evidence and the Execution examination demonstrates that our proposed plan accomplishes Attractive security andeffectiveness.
DNA computing based stream cipher for internet of things using MQTT protocol IJECEIAES
Internet of Things (IoT) is a rapidly developing technology that enables “devices” to communicate and share information amongst them without human control. The devices have the features of internet connectivity and networking. Due to the increasing demands of a secure environment in IoT application, security has become a crucial aspect on which researchers have been increasingly focused. Connecting devices to the internet can facilitate intruders to attack devices as they can access the data from anywhere in the globe. In this work, an encryption–decryption process-based stream cipher has been used. The messages between IoT nodes were encrypted using One Time Pad (OTP) and DNA computing. Furthermore, the required key sequence was generated using a linear feedback shift register (LFSR) as a pseudo number key generator. This key sequence was combined to generate a unique key for each message. The algorithm was implemented using source python and tested on a Raspberry pi under Linux open operation system.
Internet Of Things(IoT) is emerging technology in future world.The term IoT comprises of Cloud computing, Data mining,
Big data analytics, hardware board. The Security and Interoperability is a main factor that influences the IoT Enegy
consumption is also main fator for IoT application designing.The various protocols such as MQTT,AMQP,XMPP are used in
IoT.This paper analysis the various protocols used in Internet of Things.
Data Modelling and Knowledge Engineering for the Internet of ThingsCory Andrew Henson
Tutorial on Data Modelling and Knowledge Engineering for the Internet of Things, presented at EKAW 2012, Galway City, Ireland, October 8-12, 2012
http://knoesis.org/iot-tutorial-ekaw2012/
Internet of Things (IoT) plays a vital role in our
day to day life and normally used in our houses, in industry,
schools and in hospitals which implemented outside to manage
and control for taking report the changes in location prevent
from dangers and many more favorable things. Moreover all
other advantages can approach of big risks of privacy loss and
security issues. To protect the IoT devices, so many research
works have been measure to find those problems and locate a
best way to eradicate those risks or at least to reduce their effect
on the security and privacy requirement. Formation the concept
of device to device (D2D) communication technology, IoT plays
the information transfer from one end to another end as node of
interconnection. This paper examines the constraints and
security challenges posed by IoT connected devices and the
ability to connect, communicate with, and remotely manage an
incalculable number of networked, automated devices via the
Internet is becoming pervasive.
Ensemble of Probabilistic Learning Networks for IoT Edge Intrusion Detection IJCNCJournal
This paper proposes an intelligent and compact machine learning model for IoT intrusion detection using an ensemble of semi-parametric models with Ada boost. The proposed model provides an adequate realtime intrusion detection at an affordable computational complexity suitable for the IoT edge networks. The proposed model is evaluated against other comparable models using the benchmark data on IoT-IDS and shows comparable performance with reduced computations as required.
A novel architecture for lightweight block cipher, piccoloeSAT Journals
Abstract Security and privacy are going to be the key factors for the deployment of new applications, since people will only accept these deployments if these are based on secure, trustworthy and privacy-preserving infra-structures. Cryptography plays a major role in the security of data transmission and the development of computing technology imposes stronger requirements on the cryptography schemes. Lightweight cryptography is a cryptographic algorithm or protocol tailored for implementation in constrained environments including RFID tags, sensors, contactless smart cards, health-care devices and so on. These devices are leading to an ever increasing need to provide security. In order to satisfy these needs, secure and efficient encryption and authentication schemes have to be developed. Symmetric-key algorithms, especially lightweight block ciphers, play an important role to provide security in these applications. Piccolo is a new lightweight block cipher which is optimized for extremely constrained devices. Piccolo supports 64-bit block with 80 or 128-bit keys, and has an iterative structure which is a variant of a generalized Feistel network. Piccolo achieves both high security and extremely compact implementation unlike the other Feistel-type structure based lightweight block ciphers. The proposed system deals with an efficient implementation of Piccolo block cipher architecture that will fulfill mandatory requirements such as throughput and speed for low-resource devices like RFID tags and wireless sensors. The new architecture is designed such that it shares the key scheduling block for two plain text blocks concurrently. Key Words: Lightweight Cryptography, RFID, Piccolo, and Fiestel Networks.
Stylam, one of the top 3 laminate exporters
in India, has a strong presence in both domestic and
international market (contributes 70% in total revenue). The
company is doubling its capacity at a capex of Rs600 mn,
likely to complete by 2016. Total capacity would increase
to over 12 mn sheets post expansion. Total capacity would
increase to over 12 mn sheets post expansion. The company
expects utilization to reach 50% for new plant within a
period of six months due to introduction of new product
(14ftX6ft wider sheet) which has strong demand in export
market and commands a premium of 10%-15% from
regular products. Further, the company is strengthening its
presence in domestic market with direct penetration
(gradually phasing out distributors), giving better margin
and higher brand recall
2015 12 15_green_life dani da greenlife a #greenleather2016greenLIFE project
Dal convegno #greenleather2016, dello scorso 15 Dicembre 2015, le slide della relazione presentata da Guido Zilli di Conceria Dani dal titolo: Da greenLIFE a #greenleather2016
2015 12 15_GreenLIFE GRUPPO MASTROTTO sottoprodotti conciari ad alto valore a...greenLIFE project
Dal convegno #greenleather2016 organizzato da greenLIFE project lo scorso 15 Dicembre 2015, le slide della relazione di GRUPPO MASTROTTO, presentata da Andrea Loi. Il titolo dell'intervento: sottoprodotti conciari ad alto valore aggiunto per impieghi in tecnologie biocompatibili e biosostenibili
Some problems can only be solved by looking across a complete compute ecosystem. IoT Devices, Mobile Devices, Media Servers Gateways, Cloud Edge Devices.

IoT ( M2M) - Big Data - Analytics: Emulation and DemonstrationCHAKER ALLAOUI
Study and simulation of the systems modern IoT with examples of connected objects such as: GPS(GLOBAL POSITIONING SYSTEM), Philips Hue, Thermometer, and connected cars implemented with the technology nodeJS and Node-Red with the communication protocol of M2M ( MQTT).
As well as an analytical study based on Elasticsearch, MongoDB, Apache Hadoop, Apache Hive and Jaspersoft.
The Internet of things describes physical objects that are embedded with sensors, processing ability, software, and other technologies that connect and exchange data with other devices and systems over the Internet or other communications networks.
Building a reliable and scalable IoT platform with MongoDB and HiveMQDominik Obermaier
Today’s Internet of Things (IoT) is enabling companies to blend together the physical and digital worlds, creating new business models and generating insights that increase productivity at once unimaginable levels. However, managing the ever growing volume of heterogeneous IoT data from disparate devices, systems and applications both on premise and in the cloud can be a challenging endeavour without a scalable and reliable IoT platform.
In this webinar, we will explore why and how companies are leveraging HiveMQ and MongoDB to build exactly that: a scalable and reliable IoT platform. Based upon a sample fleet management scenario, we will explain how telematics data can be routed via MQTT and efficiently stored to provide analytics and insights into the data.
Key Learnings
- Common challenges and pitfalls of IoT projects
- Required components for effectively handling data with an IoT platform
- HiveMQ for MQTT to enable bi-directional device communication over unstable networks
- MongoDB as the flexible and scalable modern data platform combining data from different sources and powering your applications
- Why MongoDB and HiveMQ is such a great combination
Adequate Infosoft is one of the best IOT Software Development company here you will get the best Iot Software Developers . Visit website for more details : https://www.adequateinfosoft.com/IoT-development-company
Best Skills in Developer of IOT Software in Adequate Infosoft.pdfNishaadequateinfosof
Adequate Infosoft is one of the best IT Solution providing company here you will get the best Iot software developer . visit website for more details : https://www.adequateinfosoft.com/
What if Things Start to Think - Artificial Intelligence in IoTMuralidhar Somisetty
Artificial intelligence will be functionally necessary to wield the vast number of connected “things” online, and will be even more important in making sense of an almost endless sea of data streamed in from these devices.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
2. About US
Mahdi Hosseini Moghaddam
Education:
Industrial Experiences:
Milad Movahedin
Education:
Industrial Experiences:
3. Goal of This Presentation
Is not:
◦ Business model of IoT
◦ Security of IoT
◦ Application of IoT
Is:
◦ A general architecture for IoT
◦ How to Create a prototype
◦ An overview of some IoT platform
◦ More suitable programming language for IoT
4. Caution
oI cannot explain everything
oYou cannot get every detail
oTry to get a big picture
oGet some useful keyword
oConnect it with your daily work
5. Definitions
Internet of things: that we refer to this as IoT.
Wireless Sensor Network: that we refer to this as WSN.
Machine learning: that we refer to this as ML, is a system that can learn from data
Embedded System: is a sort of computer system often with real-time computing constraints.
6. Content of this presentation
IoT Overview
IoT Architecture
◦ Hardware device
◦ Protocols
◦ Platforms
◦ Etc
Open source Platforms
Programming Languages of choice
Demo
7. Introduction
• The term Internet of Things was first used
by Kevin Ashton in 1999.
• Refers to uniquely identifiable objects
(things) and their virtual representations in
an Internet-like structure
11. Wireless Sensor Network
• The networks typically run Low Power
Devices
• Consist of one or more sensors, could be
different type of sensors (or actuators)
14. Device Layer
oDevices are the ‘things’ of Internet of Things. Every device around us has a potential to connect
to internet and provide us with some useful information.
oEmbedded device has a chip or a circuitry called microcontroller that has all the necessary
ingredients to power or control the device. Ingredients typically include a memory chip, an
embedded processor , IO and network ports etc.
oIt may also have a small OS running like Linux that enables us to drive the device. The ability to
control the device and make it talk to the network is one of key aspects in IoT .
16. Sensors
oSensors are devices that detect events and
read changes in its environment.
oThe sensed information can be viewed in a
console connected to another device like
desktop or mobile. Sensors come in
connected form and a single form.
oConnected sensors are network of sensor
nodes that capture information from the
physical object or resource within a
particular area and send it across over the
network
17. Tagged Devices
oRadio Frequency Identification (RFID) tags
are smart bar codes that identifies the
device or a product and works in
conjunction with the RFID reader to track
the product information and send it
across the network.
oNear Field Communication (NFC) enables
devices to communicate with each other
over shorter radio frequencies. It works
more like RFID, but the device with NFC
protocol can act both as a reader and a
tag and therefore it can also be used as a
two way communication.
23. Application Protocol
MQTT: MQ Telemetry Transport (MQTT) is a lightweight message oriented middleware (MOM) that is
based on publish/subscribe model. The protocol is designed to be used for machine- to-machine
communication that involves small data footprint.
CoAP: The Constrained Application Protocol (CoAP), as the name suggests it is a protocol used with
resource constrained devices and networks.
AMQP: Advanced Message Queuing Protocol (AMQP) is another popular message oriented
middleware that has slowly made its place in the world of IoT . The protocol supports both queue
based and pub/sub messaging model.
AllJoyn: AllJoyn is a collaborative open-source software framework that makes it easy for devices to
discover , publish/broadcast itself and communicate with each other . AllJoyn was created to
promote interoperability and seamless integration between devices and application through a set of
core features.
DDS: DDS (Data Connectivity Standard) is part of OMG IoT standards, which enables network
interoperability for connected machines, enterprise systems, and mobile device.
29. MQTT(2)
oMessage Queueing Telemetry Transport
oA lightweight publish/subscribe protocol standard for traditional networks
oData-centric – Separates Data (Payload) from Metadata (Topic)
30. MQTT Topics & Wildcards
Topics are hierarchical (like filesystem path):
– /wsn/sensor/R1/temperature
– /wsn/sensor/R1/pressure
– /wsn/sensor/R2/temperature
– /wsn/sensor/R2/pressure
A Subscriber can use wildcards in topics:
– /wsn/sensor/+/temperature
– /wsn/sensor/R1/+
– /wsn/sensor/#
33. MQTT - Clean Session flag
When CONNECT-ing to the MQTT Broker the
client can say:
– CleanSession = 1
o Forget all the session settings and subscriptions on connect and disconnect
o So essentially every reconnect will be like a new session
– CleanSession = 0
Do not clean
34. MQTT - Retain flag
oIf message PUBLISH-ed with Retain flag set to 1 - the MQTT broker will remember it as a last
published value on the topic.
oThis is useful for systems with low update frequency, so new clients will not need to wait for last
known value.
35. MQTT over WebSocket
oMQTT for the browsers
oJavaScript API
oSend MQTT packets over WS frames
oSupport binary data
oFallbacks for older browsers w/o WS support
37. MQTT-S Overview
oDesigned to be very similar to MQTT.
– i.e. uses MQTT semantics
oClients are WSN nodes, which communicate via a gateway to a broker on IP network.
oThe gateway may just translate messages between MQTT-S and MQTT , so the broker is a
normal MQTT broker.
oDesigned to work on any WSN architecture/transport.
40. Core Platform Layer
The core platform layer provides a set of capabilities to connect, collect, monitor and control millions
of devices. Core platform consists of:
oProtocol Gateway: Typically the communication is channelized to the messaging platform or
middleware like MQTT or AQMP .
oIoT Messaging Middleware: Messaging middleware is a software or an appliance that allows senders
(publishers) and receivers (consumer’ s consuming the information) to distribute messages in a
loosely coupled manner without physically connected to each other.
oData Storage: The data storage component deals with storage of continuous stream of data from
devices. Typically, a NoSQL database or high performance optimized storage is used for storing data.
oData Aggregation and filter: The IoT core platform deals with raw data coming from multiple devices
and not all data needs to be consumed and treated equally by your application. As part of your IoT
application, you need to design this carefully as what data needs to be consumed and what data
might not be relevant in that context.
41. Analytics Platform Layer
The Analytics platform layer provides a set of key capabilities to analyze large volumes of
information, derive insights and enable applications to take required action.
oStream Processing: Real time stream processing is about processing streams of data from
devices (or any source) in real time, analyze the information, do computations and trigger
events for required actions. Stream processing platform like Apache Spark Streaming enables
you to write stream jobs to process streaming data using Spark API.
oMachine Learning: Machine learning process typically consists of 4 phases understanding the
problem definition and the expected business outcome, data cleansing and analysis, model
creation, training and evaluation. This is an iterative process where models are continuously
refined to improve its accuracy.
42. Cognitive Platform Layer
oCognitive computing are systems that are designed to make computers think and learn like
human brain. Such a system is trained on a set of information or data, so that it can understand
the context and help in making informed decisions.
oCognitive systems in the context of IoT would play a key role in future. Imagine 10 years down
the line where every piece of system is connected to the internet and probably an integral part
of everyday lives and information being shared continuously, how you would like to interact with
these smart devices which surround you.
oA good example can be of a connected car. As soon as you enter the car it should recognize you
automatically, adjust your car seats, start the car and start reading your priority emails. This is
not programmed but learned over a time. The car over a period of time should also provide
recommendations on how to improve the mileage based on your driving patterns.
44. Solution Layer(2)
oSolution Templates are common set of services which are developed for specific or generalized
use case that provides a head start to build IoT applications and are extended to build custom
IoT applications.
oAs an example, for a connected car solution, the abstract data model could be a vehicle’ s
runtime data + GPS data + asset data of the vehicle, which constitutes the device metamodel
and the application data model.
oOne can use solution templates to build application based on customer requirements.
45. IoT Security and Management
an enterprise IoT stack need to provide a set of capabilities which would ease the overall
process and take care of end to end cross cutting concerns like security and performance.
oDevice Management: Device management includes aspects like device registration, secure
device provisioning and access from device to cloud platform and cloud platform to device,
monitoring and administration, troubleshooting and pushing firmware and software updates to
devices including gateway.
oMonitoring and administration: Monitoring and administration is about managing the lifecycle
of the device. The lifecycle operations include register, start, pause, stop activities and the ability
to trigger events/commands to and from devices.
oDeployment: Deployment of IoT applications needs to be looked at holistically, right from IoT
devices, networks and topology, cloud services and end solutions and taking care of end to end
security.
47. Open Source Device SDKs
The open source IoT platform provides support for wide variety of protocols like MQTT, AXMP
and HTTP protocol. For MQTT , we can leverage the Eclipse based Paho library for connecting
any device to the core platform or open source library like cyclon.js which makes it easier to
connect various devices using Node.js. We really liked the cyclone.js library and the extensions
provided by the library to support various devices.
48. Apache Kafka
Apache Kafka service provides us with a highly scalable, low latency, fast and distributed publish-
subscribe messaging system. Similar to any publish-subscribe messaging system, Kafka maintains
feeds of messages in categories called topics. Producers publish data to topics and consumers
subscribe to topics to read messages. Kafka can retain messages after the specified time interval
has elapsed, unlike other messaging system which deletes messages as soon as they are
consumed.
49. Cassandra
Apache Cassandra can be used for storing the continuous stream of data coming from devices.
Kafka consumer can be created in order to listens to a specified topic, consumes the message
and stores the message in one of the Cassandra tables. Cassandra also can be used for historical
data analysis to gain insights on various usages, aggregations and computations, build
correlations and to develop our machine learning models iteratively for anomaly detection and
predictive analytics.
50. ApacheSpark Streaming
Apache Spark streaming component from Apache Spark project adds real time data stream
processing and data transformation for further processing by systems. It provides stack of
libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark
Streaming. Apache Spark streaming supports real time processing as well as batch updates on
top of Spark engine, which makes it perfect choice for applications which requires responding to
real time events and batch processing via Hadoop jobs for complex data analysis.
51. ApacheSpark MLlib
Apache Spark MLlib service is used to build machine learning models or combine multiple
machine learning models using a standardized API. Building a machine learning models require a
series of step as discussed earlier –like cleansing and transformation, creating feature vectors,
correlation, splitting up data in training and test sets, selecting algorithms for building up
required models (prediction, classification, regression, etc.) and iteratively training the model for
required accuracy.
52. Custom Rules and Events
Apache Zeppelin project can be used to quickly build an interactive data analytics dashboard.
Zeppelin has built-in support for Spark integration and SparkSQL.
54. C
It makes sense that a language first
developed to program telephone
switches would be a reasonable choice
for embedded system development. It's
available on nearly every advanced
embedded system platform that exists.
For some platforms where it's not
directly available, it's still the basis for
the dedicated language used in the
SDK.
55. C++
When the programming world began
moving toward object-oriented
languages in the early 1980s,
procedural languages such as Fortran,
Cobol, and C seemed destined to fade
into obscurity. C++ kept the spare
nature of C but added data abstraction,
classes, and objects. All of these
features make C++ a popular choice for
those who are writing embedded and
IoT code for Linux systems.
56. JAVA
Java was written to be an object-
oriented language that is incredibly
portable: There are very, very few
hardware dependencies built into the
compiler. In order to get the specific,
fine control over particular pieces of
hardware, Java depends on hardware-
support libraries that are called from
the generic code.
57. JavaScript
JavaScript is, as the name implies, a
scripting language that is heavily used
for building Web-fronted applications. If
you wanted to use the Apache server
on a Raspberry Pi to gather data from a
network of Arduino-based sensors, for
example, JavaScript would be a good
starting point for the effort.
58. Python
Python has become one of the "go-to"
languages in Web development, and its
use has spread to the embedded
control and IoT world. Python is very
flexible in many ways. For example, it is
an interpreted language that can either
be submitted to a run-time compiler or
run through one of several pre-
compilers so that compact executable
code may be distributed.
The thing that makes Python good for
programming teams, though, is its
emphasis on readability.
59. GO
Go was developed at Google and is
available on a wide variety of
processors and platforms. While it is
one of the many languages that owes a
debt to C, there are a number of ways
in which it's superior to C for certain
types of embedded programming.
Go supports concurrent input, output,
and processing on many different
channels. Used correctly, this allows the
coordination of an entire fleet of
sensors and actuators.
60. RUST
Rust was developed at Mozilla. Like the
rest of Mozilla's software, Rust is an open
source project that is evolving quickly.
Rust shares many of Go's qualities,
though it does solve one major problem
of Go. Because Go doesn't automatically
share information between the different
"channel" data structures, a program can
develop something called a "race
condition." It's basically a runaway
situation in which a system can spiral out
of control because different processes are
working at odds with one another. Rust
includes functions that eliminate race
conditions, making it a less-risky language
than Go for highly concurrent programs.
61. Erlang
Erlang is a multi-purpose programming
language used primarily for developing
concurrent and distributed systems. It
began as a proprietary programming
language used by Ericsson for
telephony and communications
applications. Released as open source
in 1998, Erlang has become more
popular in recent years thanks to its use
in high profile projects, such as the
Facebook chat system, and in
innovative open source projects, such
as the CouchDB document-oriented
database management system.
62. Erlang(2)
oIdeal platform for Large-Scale (C1M to C10M) PubSub systems
oIdeal for implementation of Gateways & Proxies
oEasy ZigBee, MQTT & MQTT-S protocol handling using bit-syntax & binary comprehensions
oVery easy to port to ARM-based Embedded Linux systems (not only RPi & BeagleBone/Board,
but also professional SBCs)
oUnique concurrency support
oPerfect for messaging platform
63. Julia
Julia is a high-level, high-performance
dynamic programming language for
technical computing, with syntax that is
familiar to users of other technical
computing environments. It provides a
sophisticated compiler, distributed
parallel execution, numerical accuracy,
and an extensive mathematical
function library.