This presentation describes the implementation of the Internet of Things(IoT) in the Oil and Gas industry. It also tells about the benefits of implementing IoT in this industry.
The document discusses key concepts in Internet of Things (IoT) design including:
1) Defining IoT as physical objects connected to the internet via sensors and controllers.
2) The importance of usability (UI/UX design) and designing for both physical appearance and logical functionality.
3) Approaches like "calm technology" that engages users' peripheral attention in a subtle rather than obtrusive way.
1) The document discusses machine learning and the Internet of Things. It defines the Internet of Things as physical objects embedded with electronics, software, and sensors that can exchange data to provide added value and services.
2) It describes how machine learning, a key tool in artificial intelligence, uses algorithms that improve at tasks through experience with data. Deep learning uses multiple layers of neurons to learn complex representations from data.
3) The document outlines an end-to-end machine learning workflow for IoT applications, including data acquisition, annotation, model training/validation/deployment, and monitoring model performance over time using new data.
The legacy of industrial based networks is now evolving into the data infrastructure layer of the, 'Internet Of Things. With billions of devices about to be connected to the internet, there are signs of a convergence. A convergence between industrial and consumer, physical and virtual, man and machine. Everyday activities in the real world will have the potential to be augmented, improved and integrated into our digital lives by means of a smooth, flawless user experience. Welcome to the Internet Of Things.
The document discusses the evolution of the internet from static Web 1.0 pages to today's dynamic Web 2.0 and upcoming Web 3.0. It defines the Internet of Things (IoT) as connecting physical objects through sensors and internet connectivity. Examples discussed include connecting devices in homes, cities, healthcare, mining and law enforcement. Challenges of IoT include bandwidth, power consumption, security and data management. Standards organizations are working to address these issues and advance IoT technologies. The future may see an "Internet of Everything" connecting people, processes, data and physical things.
This document discusses IoT networking and quality of service (QoS) for IoT networks. It begins by describing the characteristics of IoT devices such as low processing power, small size, and energy constraints. It then discusses enabling the classical Internet for IoT devices through standards developed by the IETF, including 6LoWPAN, ROLL, and CoRE. CoRE provides a framework for IoT applications and services discovery. The document concludes by examining policies for QoS in IoT networks to guarantee intended service, covering resource utilization, data timeliness, availability, and delivery.
The document discusses key concepts in Internet of Things (IoT) design including:
1) Defining IoT as physical objects connected to the internet via sensors and controllers.
2) The importance of usability (UI/UX design) and designing for both physical appearance and logical functionality.
3) Approaches like "calm technology" that engages users' peripheral attention in a subtle rather than obtrusive way.
1) The document discusses machine learning and the Internet of Things. It defines the Internet of Things as physical objects embedded with electronics, software, and sensors that can exchange data to provide added value and services.
2) It describes how machine learning, a key tool in artificial intelligence, uses algorithms that improve at tasks through experience with data. Deep learning uses multiple layers of neurons to learn complex representations from data.
3) The document outlines an end-to-end machine learning workflow for IoT applications, including data acquisition, annotation, model training/validation/deployment, and monitoring model performance over time using new data.
The legacy of industrial based networks is now evolving into the data infrastructure layer of the, 'Internet Of Things. With billions of devices about to be connected to the internet, there are signs of a convergence. A convergence between industrial and consumer, physical and virtual, man and machine. Everyday activities in the real world will have the potential to be augmented, improved and integrated into our digital lives by means of a smooth, flawless user experience. Welcome to the Internet Of Things.
The document discusses the evolution of the internet from static Web 1.0 pages to today's dynamic Web 2.0 and upcoming Web 3.0. It defines the Internet of Things (IoT) as connecting physical objects through sensors and internet connectivity. Examples discussed include connecting devices in homes, cities, healthcare, mining and law enforcement. Challenges of IoT include bandwidth, power consumption, security and data management. Standards organizations are working to address these issues and advance IoT technologies. The future may see an "Internet of Everything" connecting people, processes, data and physical things.
This document discusses IoT networking and quality of service (QoS) for IoT networks. It begins by describing the characteristics of IoT devices such as low processing power, small size, and energy constraints. It then discusses enabling the classical Internet for IoT devices through standards developed by the IETF, including 6LoWPAN, ROLL, and CoRE. CoRE provides a framework for IoT applications and services discovery. The document concludes by examining policies for QoS in IoT networks to guarantee intended service, covering resource utilization, data timeliness, availability, and delivery.
The document provides an overview of the Industrial Internet of Things (IIoT) market. Some key points:
- The IIoT market is expected to be worth $135 billion in 2016 and reach $590 billion by 2022, growing at a CAGR of 28.26%.
- Major drivers include optimizing asset utilization, reducing costs, and creating new revenue streams. Restraints include security/privacy concerns and lack of standards.
- The US is projected to gain $6.1 trillion in GDP by 2030 from IIoT, while China could gain $1.8 trillion with enhanced investments and measures.
- The market can be segmented by services, software, platforms
The document discusses the Web of Things and Cloud of Things. It describes the Web of Things as using existing web standards to simplify creating IoT applications by allowing real-world objects to be part of the World Wide Web. The Cloud of Things leverages cloud computing technologies to support the IoT. Standards like SOA and middleware platforms are discussed as ways to provide unified architectures for the Web and Cloud of Things.
The document discusses various building blocks for Internet of Things (IoT) systems, including nodes, operating systems, networks, middleware and platforms. It outlines that initial IoT systems will likely be built from the bottom up using device nodes. It also notes that node operating systems and middleware are becoming more available. Ultimately, IoT platforms aim to make developing, deploying and managing large-scale IoT systems easier by providing interoperability across different systems through standards. The document provides examples and diagrams related to each building block.
The internet of things (IoT) is the internetworking of physical devices, vehicles, buildings and other items—embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data.
The Internet of Things (IoT) is a network of physical objects embedded with electronics, software, and sensors that allows objects to connect and exchange data over the internet. IoT creates opportunities to remotely sense and control objects across networks, improving efficiency. Things in IoT include devices like heart monitors, farm animal tags, sensors in cars, and environmental sensors. These devices collect data using technologies and autonomously share it. IoT requires connectivity between things, intelligence to interpret sensor data, and scalability to handle increased connections.
A Reference architecture for the Internet of things WSO2
This document discusses WSO2 products and capabilities. It mentions several WSO2 products and services for API management, integration, and identity and access management. It concludes by inviting the reader to contact them for more information on how WSO2 products can address their needs.
This document discusses ethical issues related to smart technology in IoT. It begins with an introduction to IoT, architecture, and privacy/security concerns. It then examines stakeholders and their interests/risks. Resolutions discussed include security measures at different layers and increasing user awareness. Two specific examples are analyzed: a teddy bear hack that leaked personal recordings, and Fitbit sharing customer health data. Considerations for dealing with ethical issues include regulations, following ethics codes, customer benefit, and security improvements. Examples of IoT uses in business and related incidents/vulnerabilities are also summarized.
The document discusses the architecture of the Internet of Things (IoT). It describes the IoT as a network of physical objects embedded with sensors that can collect and exchange data. The document outlines the history and development of IoT and describes its layered architecture which includes device, network, service, and application layers. It provides examples of current and potential IoT applications in various sectors and discusses security and privacy issues regarding connected devices.
An introductory video and presentation looking at Internet of Things (IoT) and differences between IoT and #IIoT. Examples are provided to help clarify the understanding.
IoT - Data Management Trends, Best Practices, & Use CasesCloudera, Inc.
With billions of new devices, IoT is transforming how businesses capitalize on data. Data driven organizations are using IoT as as a means to improve their customer experience, drive operational efficiencies, and enable new business models. However, without the right data management strategy and tools, investments in IoT can yield limited results.
Join Cloudera and 451 Research for a joint webinar to learn more about some of the data management best practices and how organizations are using advanced analytics and machine learning to enable IoT use cases.
A talk presented at IEEE ComSoc workshop on Evolution of Data-centers in the context of 5G.
Discuss about what is edge computing and management issues in Edge Computing
This document is a report on the Internet of Things (IoT) written by Rohit Mahali for his mentor Mr. Biswanath Sethi. The report defines IoT as connected devices that can collect and exchange data without human intervention. It discusses why IoT is useful for automation and remote control. Examples are given of applications in various industries. Challenges of IoT include connectivity, security, and managing large amounts of collected data in the cloud. The conclusion is that while complex, IoT has potential to transform many businesses and lives.
The term “fog computing” or “edge computing” means that rather than hosting and working from a centralized cloud, fog systems operate on network ends. It is a term for placing some processes and resources at the edge of the cloud, instead of establishing channels for cloud storage and utilization.
IoT Solutions for Smart Energy Smart Grid and Smart Utility ApplicationsEurotech
Smart Energy Smart Grid and Smart Infrastructure - Many Applications and Devices
An introduction to Eurotech' s IoT Field-to-Application Building Blocks for the Energy and Utility Industry
What we got covered?
1) What Is Industrial IoT
2) Application of Industrial IOT
3) Machine To Machine (M2M)
4) Benefits of Industrial IoT
5) Vendors in Industrial IoT
6) Features of Industrial IoT
This document discusses machine-to-machine (M2M) communication and its differences from the Internet of Things (IoT). It also describes software-defined networking (SDN) and network function virtualization (NFV) and their potential applications to IoT. M2M uses local area networks with proprietary protocols while IoT connects devices globally using IP. SDN separates the control plane from the data plane to simplify network management while NFV virtualizes network functions on commodity servers.
Vijayanand Metri presented a seminar on wireless sensor networks under the guidance of Prof. Surekha of the computer science and engineering department at GEC Haveri. The presentation covered the introduction, architecture, types, characteristics, features, issues, applications, advantages, and disadvantages of wireless sensor networks. It discussed sensor nodes, ad hoc deployment, unattended operation, environmental monitoring, health monitoring, and concluded that WSNs consist of small sensor nodes that can solve many open issues practically and cost-effectively.
Industry 4.0 has widespread application across Industries (Manufacturing, Logistics, Mobility etc.). In case of manufacturing and processing industries Industry 4.0 means Smart Manufacturing using IIoT (Industrial Internet of Things or simply Industrial IoT) in a connected smart factory.
It enables an Organization to make smart data-driven decisions based on Big Data, Artificial Intelligence and Machine Learning. Industry 4.0 IIoT has several benefits such as Resource Optimization, Cost Reduction, Automation, Predictive Maintenance and Prescriptive Analytics and Control etc.
The document describes the iCore project which aims to develop an open cognitive framework for empowering the Internet of Things. It discusses:
- The project details including partners, duration, budget.
- The iCore concept of virtual and composite virtual objects to represent real and digital objects.
- The technical challenges of addressing interoperability, reusability, reliability and energy efficiency.
- The technical approach including cognitive mechanisms, semantic descriptions and context awareness.
- The work organization split into clusters for technology, implementation, use case definition and management.
- Potential application domains and example use cases like smart cities, transport, homes and businesses.
- Engagement of an external stakeholders group
Digital twins are precise virtual representations of physical objects that use collected data from sensors to display information. They consist of a physical object, its virtual twin, and the data connection between them. By 2021, half of large industrial companies are expected to use digital twins, improving effectiveness by 10%. Digital twins have various applications and allow real-time updates, data analysis, and product optimization. However, they require constant sensor data, large datasets, and internet connectivity to achieve full accuracy.
RTMS is a tank monitoring and distribution optimization solution outlined to enable distributors of gases and fuels and any other fluid to remotely analyze tank fill levels.
industrial IoT can monitor critical machineryDan Yarmoluk
This document discusses how the Industrial Internet of Things (IIoT) can help manufacturers monitor critical machinery to improve efficiency and reduce costs. Key points:
1) The IIoT connects industrial systems and uses data analytics to enable predictive maintenance and minimize downtime.
2) Sensors can monitor things like pumps, valves, inventory levels and send real-time alerts about performance issues before failures occur.
3) This predictive maintenance and visibility into operations helps reduce costs, maximize productivity, and improve customer service by preventing production delays.
The document provides an overview of the Industrial Internet of Things (IIoT) market. Some key points:
- The IIoT market is expected to be worth $135 billion in 2016 and reach $590 billion by 2022, growing at a CAGR of 28.26%.
- Major drivers include optimizing asset utilization, reducing costs, and creating new revenue streams. Restraints include security/privacy concerns and lack of standards.
- The US is projected to gain $6.1 trillion in GDP by 2030 from IIoT, while China could gain $1.8 trillion with enhanced investments and measures.
- The market can be segmented by services, software, platforms
The document discusses the Web of Things and Cloud of Things. It describes the Web of Things as using existing web standards to simplify creating IoT applications by allowing real-world objects to be part of the World Wide Web. The Cloud of Things leverages cloud computing technologies to support the IoT. Standards like SOA and middleware platforms are discussed as ways to provide unified architectures for the Web and Cloud of Things.
The document discusses various building blocks for Internet of Things (IoT) systems, including nodes, operating systems, networks, middleware and platforms. It outlines that initial IoT systems will likely be built from the bottom up using device nodes. It also notes that node operating systems and middleware are becoming more available. Ultimately, IoT platforms aim to make developing, deploying and managing large-scale IoT systems easier by providing interoperability across different systems through standards. The document provides examples and diagrams related to each building block.
The internet of things (IoT) is the internetworking of physical devices, vehicles, buildings and other items—embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data.
The Internet of Things (IoT) is a network of physical objects embedded with electronics, software, and sensors that allows objects to connect and exchange data over the internet. IoT creates opportunities to remotely sense and control objects across networks, improving efficiency. Things in IoT include devices like heart monitors, farm animal tags, sensors in cars, and environmental sensors. These devices collect data using technologies and autonomously share it. IoT requires connectivity between things, intelligence to interpret sensor data, and scalability to handle increased connections.
A Reference architecture for the Internet of things WSO2
This document discusses WSO2 products and capabilities. It mentions several WSO2 products and services for API management, integration, and identity and access management. It concludes by inviting the reader to contact them for more information on how WSO2 products can address their needs.
This document discusses ethical issues related to smart technology in IoT. It begins with an introduction to IoT, architecture, and privacy/security concerns. It then examines stakeholders and their interests/risks. Resolutions discussed include security measures at different layers and increasing user awareness. Two specific examples are analyzed: a teddy bear hack that leaked personal recordings, and Fitbit sharing customer health data. Considerations for dealing with ethical issues include regulations, following ethics codes, customer benefit, and security improvements. Examples of IoT uses in business and related incidents/vulnerabilities are also summarized.
The document discusses the architecture of the Internet of Things (IoT). It describes the IoT as a network of physical objects embedded with sensors that can collect and exchange data. The document outlines the history and development of IoT and describes its layered architecture which includes device, network, service, and application layers. It provides examples of current and potential IoT applications in various sectors and discusses security and privacy issues regarding connected devices.
An introductory video and presentation looking at Internet of Things (IoT) and differences between IoT and #IIoT. Examples are provided to help clarify the understanding.
IoT - Data Management Trends, Best Practices, & Use CasesCloudera, Inc.
With billions of new devices, IoT is transforming how businesses capitalize on data. Data driven organizations are using IoT as as a means to improve their customer experience, drive operational efficiencies, and enable new business models. However, without the right data management strategy and tools, investments in IoT can yield limited results.
Join Cloudera and 451 Research for a joint webinar to learn more about some of the data management best practices and how organizations are using advanced analytics and machine learning to enable IoT use cases.
A talk presented at IEEE ComSoc workshop on Evolution of Data-centers in the context of 5G.
Discuss about what is edge computing and management issues in Edge Computing
This document is a report on the Internet of Things (IoT) written by Rohit Mahali for his mentor Mr. Biswanath Sethi. The report defines IoT as connected devices that can collect and exchange data without human intervention. It discusses why IoT is useful for automation and remote control. Examples are given of applications in various industries. Challenges of IoT include connectivity, security, and managing large amounts of collected data in the cloud. The conclusion is that while complex, IoT has potential to transform many businesses and lives.
The term “fog computing” or “edge computing” means that rather than hosting and working from a centralized cloud, fog systems operate on network ends. It is a term for placing some processes and resources at the edge of the cloud, instead of establishing channels for cloud storage and utilization.
IoT Solutions for Smart Energy Smart Grid and Smart Utility ApplicationsEurotech
Smart Energy Smart Grid and Smart Infrastructure - Many Applications and Devices
An introduction to Eurotech' s IoT Field-to-Application Building Blocks for the Energy and Utility Industry
What we got covered?
1) What Is Industrial IoT
2) Application of Industrial IOT
3) Machine To Machine (M2M)
4) Benefits of Industrial IoT
5) Vendors in Industrial IoT
6) Features of Industrial IoT
This document discusses machine-to-machine (M2M) communication and its differences from the Internet of Things (IoT). It also describes software-defined networking (SDN) and network function virtualization (NFV) and their potential applications to IoT. M2M uses local area networks with proprietary protocols while IoT connects devices globally using IP. SDN separates the control plane from the data plane to simplify network management while NFV virtualizes network functions on commodity servers.
Vijayanand Metri presented a seminar on wireless sensor networks under the guidance of Prof. Surekha of the computer science and engineering department at GEC Haveri. The presentation covered the introduction, architecture, types, characteristics, features, issues, applications, advantages, and disadvantages of wireless sensor networks. It discussed sensor nodes, ad hoc deployment, unattended operation, environmental monitoring, health monitoring, and concluded that WSNs consist of small sensor nodes that can solve many open issues practically and cost-effectively.
Industry 4.0 has widespread application across Industries (Manufacturing, Logistics, Mobility etc.). In case of manufacturing and processing industries Industry 4.0 means Smart Manufacturing using IIoT (Industrial Internet of Things or simply Industrial IoT) in a connected smart factory.
It enables an Organization to make smart data-driven decisions based on Big Data, Artificial Intelligence and Machine Learning. Industry 4.0 IIoT has several benefits such as Resource Optimization, Cost Reduction, Automation, Predictive Maintenance and Prescriptive Analytics and Control etc.
The document describes the iCore project which aims to develop an open cognitive framework for empowering the Internet of Things. It discusses:
- The project details including partners, duration, budget.
- The iCore concept of virtual and composite virtual objects to represent real and digital objects.
- The technical challenges of addressing interoperability, reusability, reliability and energy efficiency.
- The technical approach including cognitive mechanisms, semantic descriptions and context awareness.
- The work organization split into clusters for technology, implementation, use case definition and management.
- Potential application domains and example use cases like smart cities, transport, homes and businesses.
- Engagement of an external stakeholders group
Digital twins are precise virtual representations of physical objects that use collected data from sensors to display information. They consist of a physical object, its virtual twin, and the data connection between them. By 2021, half of large industrial companies are expected to use digital twins, improving effectiveness by 10%. Digital twins have various applications and allow real-time updates, data analysis, and product optimization. However, they require constant sensor data, large datasets, and internet connectivity to achieve full accuracy.
RTMS is a tank monitoring and distribution optimization solution outlined to enable distributors of gases and fuels and any other fluid to remotely analyze tank fill levels.
industrial IoT can monitor critical machineryDan Yarmoluk
This document discusses how the Industrial Internet of Things (IIoT) can help manufacturers monitor critical machinery to improve efficiency and reduce costs. Key points:
1) The IIoT connects industrial systems and uses data analytics to enable predictive maintenance and minimize downtime.
2) Sensors can monitor things like pumps, valves, inventory levels and send real-time alerts about performance issues before failures occur.
3) This predictive maintenance and visibility into operations helps reduce costs, maximize productivity, and improve customer service by preventing production delays.
IRJET- High Responsive Smart Parking System using IoTIRJET Journal
This document presents a proposed smart parking system using IoT. The system uses RFID sensors and a PIC microcontroller to detect vehicle occupancy of parking spaces in real-time. This information is sent to a cloud database. A mobile app allows drivers to check parking availability and book spaces. The system aims to address issues like inefficient parking, traffic congestion, and reduced fuel consumption by helping drivers find vacant spaces quickly. It provides real-time parking information and allows contactless payment of fees.
IoT Development In Manufacturing A Guide to Industrial Digital Transformation...Laura Miller
IoT helps manufacturers to streamline operations & boost productivity with ease. Read the blog to know how the IoT development brings digital transformation.
This document discusses applications of the Internet of Things (IoT) through a survey. It begins by defining IoT as the network of connected objects able to collect and exchange data using embedded sensors. The document then summarizes four key applications of IoT: smart homes, smart agriculture, smart cities, and smart industry. For each application, examples are provided of how IoT can be implemented such as home automation, environmental monitoring, traffic management, and machine maintenance. The survey finds that IoT has significant potential to improve efficiency and innovation across many sectors.
This document discusses the challenges of scaling IoT initiatives to generate ROI within 18 months as recommended. While IoT projects are collecting huge amounts of data across industries, only 1% of the data is being properly analyzed to produce actionable insights. This leads to 275% of IoT projects failing to achieve their financial goals due to a lack of expertise in scaling solutions to leverage the full potential of collected data through analytics and machine learning. The document promotes an innovative cloud platform to help organizations securely connect devices, scale their big data infrastructure, and generate insights to maximize ROI from IoT implementations.
IRJET- IoT based Traffic Congestion Monitoring and Management SystemIRJET Journal
This document presents a proposed IOT-based traffic congestion monitoring and management system that uses RFID technology. The system aims to provide clear paths (green waves) for emergency vehicles by turning traffic lights green on their route. It can also track stolen vehicles when they pass through traffic lights. The system uses RFID tags on vehicles to identify vehicle type and detect stolen vehicles. Sensors monitor traffic levels and an IOT unit communicates with a control unit to adjust traffic light patterns in real-time based on vehicle density. This is intended to reduce congestion and response times for emergency vehicles. The proposed system is evaluated as being economically effective for traffic management.
This document discusses applications of the Internet of Things (IoT) through a survey. It begins by introducing IoT and its ability to connect devices. The document then examines four key applications of IoT: smart homes, smart agriculture, smart cities, and smart industry. For each application, the document describes how IoT can be used, providing examples such as home automation, environmental monitoring, traffic management, and machine diagnosis. It concludes that IoT has wide-ranging potential and will continue developing innovative solutions across many domains.
The Most Definitive guide to Industrial IoT ImplementationAditya Basu
Industrial IoT has the potential of USD 15.3 trillion to the global economy by 2030 subjected to an improvement of 1-1.5%. Industrial Internet is a revolutionary technology that enhances the Industrial environment with the IoT capabilities. IIoT helps to solve the bottlenecks in the business environment, provides operational efficiency, increases productivity and reduces the complexity of the process.
The main benefit of Industrial IoT is the connected enterprise that enhances the visibility across various departments and benefits with a smooth workflow. According to General Electric CEO, Jeff Immelt, IIoT has twice the market potential than that of the consumer IoT.
In this Guide you will know everything about
a) The Connected Factory! Role of IIoT
b) Evolution of IIoT to Industry 4.0
c) Industrial IoT Ecosystem
d) Value Chain Players today and what you can learn from them
e) How IIoT is Different from IoT
f) Technology Drivers and Adoption
g) Market Indicators and why you should jump the Bandwagon NOW!
h) Market Revenues and Areas of Focus
i) The Digitization Wave
j) Real World Industrial IoT Case Studies Including Solutions & Outcomes
This document discusses Industry 4.0, which refers to the current trend of increased automation and data exchange in manufacturing technologies using cyber-physical systems, the internet of things, cloud computing, and cognitive computing. It is considered the fourth industrial revolution. The document provides an overview of the four industrial revolutions from the introduction of steam power in Industry 1.0 to the increased automation using sensors and machine learning in Industry 4.0 today. It also discusses key aspects of Industry 4.0 like cyber-physical systems, the internet of things, benefits and examples of IIoT (industrial internet of things) systems.
IRJET-Android Device for Smart Fluid Meter Reading System in IOT and WSN Envi...IRJET Journal
This document proposes an IoT and wireless sensor network based smart fluid meter reading system using an Android device. A YF-S201 fluid sensor is placed between a fluid pipe and contains a pinwheel sensor to measure fluid flow. It outputs electric pulses counted by an Arduino Nano microcontroller. Bluetooth transmits this data to an Android app for monitoring. Data is stored and analyzed on the cloud for user access from anywhere. The system provides accurate, economical fluid measurement and analysis to reduce waste and optimize consumption.
IOT Development in Manufacturing A Guide to Industrial Digital Transformation...Laura Miller
IoT helps manufacturers to streamline operations and boost productivity with ease. Read the blog to know how the IoT development brings digital transformation.
The document discusses the concepts of the Internet of Things (IoT). It defines IoT as connecting physical objects to the internet to communicate data and interact. The basic goal of IoT is to connect unconnected objects to improve efficiency and automation. Some key points discussed include:
- The genesis of IoT starting in 2008-2009 with Kevin Ashton coining the term.
- Examples of IoT applications including connected roadways using sensors in vehicles, connected factories using real-time tracking of production, and smart connected buildings using sensors to optimize HVAC and lighting.
- Convergence of IT and OT bringing together operational technology networks that monitor physical systems with traditional IT networks and data systems.
The document discusses the Internet of Things (IoT) and its impact on industry. It describes how connected devices and equipment are becoming more common in both consumer and business settings. It provides examples of how IoT is used in industries like oil and gas, agriculture, and commercial buildings. It then discusses some of the key business drivers for adopting IoT technologies, such as complying with regulations, reducing costs, differentiating products, and generating new revenue streams. Finally, it outlines some of the major barriers to wider IoT adoption, such as technology culture issues, lack of skills, misunderstanding ROI, and security concerns. It provides recommendations for how organizations can start small with IoT pilots to prove value before wider deployment.
Engineering Enablement for Connected and Intelligent SystemsCyient
The document discusses Cyient's experience developing an IoT-based tower operations center. It begins with an overview of the current IoT market and adoption challenges. It then discusses how IoT creates value through connected components that can sense, transport, store, provide insights, and enable actions. The presentation describes Cyient's journey developing an IoT solution for centralized tower monitoring and management. Key features of the tower operations center include performance monitoring, security and alarm management, usage monitoring, and inventory management. Benefits include optimizing energy usage, managing assets, automating operations remotely, and reducing operating expenses.
What Is the Role of IoT in Logistics and Transportation.pdfRosalie Lauren
In recent years, the Internet of Things (IoT) has transformed logistics and transportation. The Internet of Things (IoT) refers to the networking of devices, vehicles, and sensors that collect and share data via the internet.
The article looks at how new technologies will lead to an increasingly integrated approach within the O&G sector, siting specifics such as the IoT and robotics & the radical impact they will have on optimising productions within the sector.
In the mining and construction industries, IoT solutions using sensors and satellite connectivity can improve safety, productivity, and efficiency by enabling remote monitoring of operations and predictive maintenance of equipment. Key uses of IoT include predictive maintenance using sensor data to analyze equipment performance, fleet management and asset tracking using satellite to monitor vehicle locations, and environmental monitoring using sensors to detect issues and enable early mitigation steps. ST Engineering iDirect provides IoT solutions suitable for these industries' low, medium, and high data rate IoT use cases through their satellite terminal equipment and network platforms.
IOT SMOKE DETECTION SYSTEM USING ARDUINOIRJET Journal
This document describes an IOT smoke detection system using Arduino that detects smoke and fire using an LM35 temperature sensor. When smoke or a temperature increase indicative of fire is detected, an alert message is sent via SMS to users through a GSM module. The system uses an Arduino Uno board with an ATmega328 microcontroller to control the temperature sensor and send alerts. The goal is to provide home fire protection by quickly detecting fires and notifying people.
This presentation gives a clear and concise description of joins in sql and several types of sql joins.
These slides also contains the pictorial representation as well as syntax for each type of joins.
This document provides instructions for writing a review of one chapter from an auxiliary reading. The review must be 5-6 pages long with specific formatting and include: an introduction with the chapter's thesis, discussion of 3-4 main points from the chapter, background on the author, a personal evaluation, and a conclusion assessing if the author accomplished their purpose. The review must be the student's own writing with no more than two brief quotes cited from the chapter.
This presentation tells about the inventory models. It describes the two widely used inventory models i.e. Fixed Recorder Quantity System and Fixed Order Period System.
This describes the supervised machine learning, supervised learning categorisation( regression and classification) and their types, applications of supervised machine learning, etc.
This document discusses exception handling in Java. It defines what exceptions are, why they occur, and what exception handling is. It describes the advantages of exception handling and differences between exceptions and errors. It covers the exception class hierarchy and exception handling keywords like try, catch, finally, throw, and throws. It provides examples of common exception types and an example Java code demonstrating exception handling.
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
2. The oil and gas industry is making headway in realizing the
potential of IoT by making things much easier for companies to
carry out their daily operations.
Refining The Oil And Gas Industry With IoT
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3. Oil and Gas IoT
The oil and gas industry is an early adopter of internet of things (IoT)
technology, and for good reason. Energy providers leverage many of the
same IoT components used in other industries, including remote sensors,
machine learning and the cloud.When connected and combined with
business processes such as alerts, IoT in oil and gas systems enables
operators to monitor systems and react safely and in real time to production
issues as they arise.
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4. USING IOT IN OIL AND GAS
• Drilling Management
• Pipeline Monitoring
• Refinery Monitoring
• Offshore Monitoring
• Cargo Shipping
• Health and Safety
• Carbon Footprint Control
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5. Drilling management
• Drilling is a major part of oil and gas industry procedures.The Internet of
Things proves to be a boon for enhancing efficiency in the drilling
procedure.As the rig digs deep, it leads to potentially dangerous
circumstances. Rig operators must take precise measurements to extract oil
by drilling. If deep-water drilling is carried out in the wrong way it leads to
mishaps. IoT devices are beneficial for minimizing risks and carrying out
tough operations seamlessly. Smart devices also alert concerned personnel
well in advance about any drilling errors using the data received from
sensors.
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6. Pipeline monitoring
• Pipeline leakage is one of the major issues faced by the oil and gas industry. It
leads to major financial, environmental, and reputational damage to the
company. IoT helps monitor the pipeline system and its components like pipes,
pumps, and filters. Without IoT, companies have to rely on human resources to
carry out periodic routine checks and maintenance. IoT helps cut down on
manual checks as it can monitor pipelines in real-time.The real-time data can
help in significantly reducing major hazards that are associated with pipeline
leakages and other unwanted situations. Employees can be quickly put in use
to fix any issues which may result in significant danger.
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7. Efficient Management
• Another advantage of using IoT in the oil and gas industry is the efficient
management of employees and the plant. Employees will be required to
carry out maintenance only when an abnormality is detected.This
eliminates the need for periodic human inspection, and human resources
can be managed efficiently. Moreover, planned shutdowns and efficient
management of materials can be done using IoT.
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8. Refinery monitoring
• IoT helps monitor things like pipe pressure, flow rate, among other
performance parameters. A lot of measurement and data is required regarding
every component of the refinery.This is time-consuming and costs the
company a lot if done manually. Some areas need precise measurements in
real-time.
• For example, a certain valve may need to be controlled based on the flow-rate
monitored at some other place. In such a case, a change in the flow rate would
require an instantaneous control of the valve.
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9. • The IoT allows for more data collection accurately
at places can’t be accessed by human resources.
Sensors can be placed at various points that are
hard to access by employees and can provide
more data.This helps for the round-the-clock
monitoring of the refinery.
• According to a report, the oil and gas
companies can improve their production by 6%
to 8% with proper utilization of data.
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10. Offshore monitoring
• Most offshore oil and gas production is done in extreme environments.There
are very few communication networks available at these rigs. Monitoring
temperatures, pressures, and other equipment monitoring become a difficult
task and an expensive one too. IoT helps overcome these hurdles to provide an
efficient monitoring system.
• Using Low PoweredWide Area Network (LPWAN), a lot more monitoring points
can be connected.This implementation provides a relatively inexpensive
solution for offshore oil and gas rig monitoring. Multiple leak detectors can be
connected to oil wells within a large area. Each of these detectors can send the
data to a central point in real-time.The data can then be leveraged to monitor
the drilling and oil extraction process remotely.
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11. Cargo shipping
• Real-time ship and fleet monitoring is a very important aspect for fleet managers.
Oil and gas cargo ship monitoring is similar to its offshore equivalent.There’s no
connectivity at the ocean, and the workers have to rely on satellite internet.There
are limited options available if the workers need data from around the ship.The
data from these ships is huge in itself. IoT provides for easy data collection from
these points. LPWANs provide easy monitoring options for parts of a ship that
aren’t frequented by ship personnel. Sensory monitoring devices provide safety
as well as convenience in gathering data from points that are not easily
accessible. Some elements of cargo ships have to be wired due to real-time
needs, whereas some non-operational elements don’t need to be connected in
real-time.Therefore, small IoT networks prove to be a great alternative to wired
sensors.
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12. Health and safety
• Oil and gas sites are usually found at dangerous and remote locations.The
conditions at these sites prove to be a hazard for the employees working at these
locations. IoT solutions provide for remote monitoring of equipment and
operations, no longer requiring individuals to go to a site without prior knowledge
of the situation at hand. Connected sensors and image vision can provide an
accurate detail of the situation and help decide the safest course of action. IoT in
oil and gas can help reduce deaths and injuries caused to employees significantly.
The fatality rates among oil and gas employees are decreasing, and IoT can help
bring down the number to a greater extent. Accidents can prove to be expensive
to the companies financially as well as damage the reputation of the company. By
using IoT-enabled safety measures, oil and gas companies can provide their
workers with a safe working environment.
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13. Carbon footprint control
• The implementation of IoT in oil and gas operations results in the efficient
working of the industry. IoT solutions prove beneficial financially as well as
environmentally. With efficient management and working of the plant, the
carbon emissions generated by them can be reduced significantly. It helps
lower the environmental footprint generated by oil drilling and production
operations. Oil and gas companies can thus carry out their moral
responsibility of not impacting the environment in a harmful way while
carrying out operations.
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14. • The oil and gas industry has always faced the problem of inventory planning and
optimization. IoT helps in efficient planning and scheduling in the supply-chain
process. Refineries can use sensors to detect the blends of crude oil incoming
and the exact location where the barrels are stored.This data proves valuable for
operation and production decisions.The use of IoT in oil and gas supply
management chain brings transparency and authenticity to the industry.
Supply-chain management
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15. Increased revenue
• In recent years, the competition among oil and gas companies has been
increasing.The leading organizations are seeking strategies to help maximize
efficiency and improve their profits. Focusing on short-term cost-cutting
measures can hamper long-term business success. Investing in IoT will ensure
companies are more successful in reducing their operating costs. Improving
efficiencies, the demand and supply predictions, and streamlining expensive
processes can be achieved significantly with IoT solutions. Minimizing the
unnecessary expenditure in terms of capital and human resources can help
companies cut down on operating costs significantly.
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16. Creating ‘smart’ oil and gas will continue to be a long, evolving process. IoT
solutions are making their way from the plant to boardrooms.The use of IoT in
oil and gas is thus, not limited to only the plant and rig operations, but covers
many, if not all, aspects.The IoT and the data generated by these devices are
helping change the way the industry operates and ushering a new era of
efficiency and profitability for the companies involved.
Conclusion
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