This document discusses connected products and industrial ecosystems. It begins by explaining that manufacturers can leverage connected product ecosystems to create new business models, improve operations, and design better products aligned with customer needs. It then explores the opportunities and challenges of adopting product-centric connected ecosystems. The key elements of connected ecosystems are hardware, networks, data management, and intelligence/interaction. Connected ecosystems generate value through operational improvements, product innovation, enhanced customer experience, and new business models. However, challenges include issues around data ownership and control within these complex multi-stakeholder ecosystems.
This document provides an executive summary on the transformation of utility asset management due to new technologies like smart meters, sensors, cloud computing, predictive analytics, and the internet of things. It discusses how these technologies have created new sources of data that utilities must now integrate and analyze in real-time to improve asset management. The future of asset management will rely more on data-driven decision making using descriptive, predictive, prescriptive and adaptive analytics. This will allow utilities to move from reactive to proactive maintenance to improve reliability and reduce costs.
IRJET- A Smart Medical Monitoring Systems using Cloud Computing and Internet ...IRJET Journal
1. The document proposes a smart medical monitoring system using cloud computing and the Internet of Things. It presents an architecture called RMCPHI that uses body sensors, networks, communication modules, and cloud services to remotely monitor patient health data.
2. The RMCPHI architecture transfers sensor data through gateways to a medical information analysis platform where data is processed and statistics are generated. This allows quick decision making for remote health monitoring and management.
3. The system aims to improve remote patient monitoring by leveraging the flexible resources of cloud computing to handle large volumes of medical data generated by IoT sensors.
Pre-Covid (Novel Coronavirus), During and Post-Covid has changed everything from thinking to doing. “Smart Factory” is the basic principle of Industry 4.0 wherein new technology allowing the fusion of physical world and the digital world. Industry 4.0 encompasses the various transformations we’re experiencing in modern manufacturing process and industry landscape as a whole. Artificial Intelligent, Augmented, Virtual and Mixed Reality, Internet of Things (IoTs), Cloud Computing and Cognitive Computing have created one system to coordinate, communicate and connect Man, Machine and Method remotely.
Here, Industry 4.0 or Manufacturing 4.0 is the amalgamation of IT, ICT and Manufacturing operations. Data is a valuable asset in digital revolution and this has inspired a vision to the manufacturing industry to create a data space as a trusted field for the exchange of information across company boundaries that helps to ease the overall manufacturing and business operations.
Big data represents one of the most profound and most pervasive evolutions in the digital world. Examples of big data come from Internet of Things (IoT) devices, as well as smart cars, but also the use of social networks, industries, and so on. The sources of data are numerous and continuously increasing, and, therefore, what characterizes big data is not only the volume but also the complexity due to the heterogeneity of information that can be obtained. The fastest growth in spending on big data technologies is happening within banking, healthcare, insurance, securities and investment services, and telecommunications. Remarkably, three of those industries lie within the financial sector, which has many particularly serviceable use cases for big data analytics, such as fraud detection, risk management, and customer service optimization. In fact, the definition of big data analysis refers to the process that encompasses the gathering and analysis of big data to obtain useful information for the business. This paper focuses on delivering a short review concerning the current technologies, future perspectives, and the evaluation of some use cased associated with the analysis of big data.
The document discusses the concept of the Internet of Things (IoT), which involves connecting machines, facilities, fleets, networks, and people to sensors and controls. It notes that:
- The IoT has the potential to revolutionize how we live and do business across many industries.
- While the concept has been around since the 1990s, improving sensors, analytics, and declining costs are driving new applications in areas like automotive, healthcare, manufacturing and more.
- Companies face challenges in developing IoT strategies, integrating technologies, managing and analyzing sensor data at scale, and ensuring security and privacy.
How smart, connected products are transforming companies presentation (edit...Fahmy Amrillah
Information technology is revolutionizing products. Once composed solely of mechanical and electrical parts, products have become complex systems that combine hardware, sensors, data storage, microprocessors, software, and connectivity in myriad ways. These “smart, connected products”—made possible by vast improvements in processing power and device miniaturization and by the network benefits of ubiquitous wireless connectivity—have unleashed a new era of competition.
by Michael E. Porter and James E. Heppelmann
The document discusses applications of cyber-physical systems and robotics. Some key areas discussed include smart manufacturing using robotics working safely with humans, transportation systems using vehicle-to-vehicle communication and autonomous vehicles, smart energy grids, infrastructure monitoring using sensors, and medical devices. The integration of computation, networking, and physical processes allows innovative applications that can improve efficiency, safety, reliability and sustainability across many sectors.
The expansion of the Internet of Things IoT implies progressively dynamic client gadgets on the Internet. IoT devices can be ordinary articles from vehicles, advanced mobile phones to wearable sensors. Huge measures of information are produced by IoT devices through the assortment and transmission of information required for the yield of valuable results and in this way, an ef cient approach to work is significant. In the public eye today, mobile communication and mobile computing play a critical job in each part of our lives, both individual and open correspondence. By utilizing Cloud Computing with IoT, data computations are situated outside the devices henceforth diminishing the strain on the devices themselves. IoT devices are additionally frequently portable and with versatility comes the need to have wireless connections to the cloud. Therefore, Mobile Cloud Computing MCC gets appropriate. However, the development in mobile computing use can be improved by coordinating portable figuring into distributed computing. This will bring about developing another model called Mobile Cloud Computing MCC that has as of late pulled in a lot of consideration in the academic sector. This paper investigates its features, advantages, applications, and difficulties of Mobile Cloud Computing. Research endeavours towards the execution of Mobile Computing are additionally talked about giving an understanding of the fate of the innovation. Sujay Sudhakar Parkhe "Smart Computing: Mobile + Cloud" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30340.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/30340/smart-computing-mobile--cloud/sujay-sudhakar-parkhe
This document provides an executive summary on the transformation of utility asset management due to new technologies like smart meters, sensors, cloud computing, predictive analytics, and the internet of things. It discusses how these technologies have created new sources of data that utilities must now integrate and analyze in real-time to improve asset management. The future of asset management will rely more on data-driven decision making using descriptive, predictive, prescriptive and adaptive analytics. This will allow utilities to move from reactive to proactive maintenance to improve reliability and reduce costs.
IRJET- A Smart Medical Monitoring Systems using Cloud Computing and Internet ...IRJET Journal
1. The document proposes a smart medical monitoring system using cloud computing and the Internet of Things. It presents an architecture called RMCPHI that uses body sensors, networks, communication modules, and cloud services to remotely monitor patient health data.
2. The RMCPHI architecture transfers sensor data through gateways to a medical information analysis platform where data is processed and statistics are generated. This allows quick decision making for remote health monitoring and management.
3. The system aims to improve remote patient monitoring by leveraging the flexible resources of cloud computing to handle large volumes of medical data generated by IoT sensors.
Pre-Covid (Novel Coronavirus), During and Post-Covid has changed everything from thinking to doing. “Smart Factory” is the basic principle of Industry 4.0 wherein new technology allowing the fusion of physical world and the digital world. Industry 4.0 encompasses the various transformations we’re experiencing in modern manufacturing process and industry landscape as a whole. Artificial Intelligent, Augmented, Virtual and Mixed Reality, Internet of Things (IoTs), Cloud Computing and Cognitive Computing have created one system to coordinate, communicate and connect Man, Machine and Method remotely.
Here, Industry 4.0 or Manufacturing 4.0 is the amalgamation of IT, ICT and Manufacturing operations. Data is a valuable asset in digital revolution and this has inspired a vision to the manufacturing industry to create a data space as a trusted field for the exchange of information across company boundaries that helps to ease the overall manufacturing and business operations.
Big data represents one of the most profound and most pervasive evolutions in the digital world. Examples of big data come from Internet of Things (IoT) devices, as well as smart cars, but also the use of social networks, industries, and so on. The sources of data are numerous and continuously increasing, and, therefore, what characterizes big data is not only the volume but also the complexity due to the heterogeneity of information that can be obtained. The fastest growth in spending on big data technologies is happening within banking, healthcare, insurance, securities and investment services, and telecommunications. Remarkably, three of those industries lie within the financial sector, which has many particularly serviceable use cases for big data analytics, such as fraud detection, risk management, and customer service optimization. In fact, the definition of big data analysis refers to the process that encompasses the gathering and analysis of big data to obtain useful information for the business. This paper focuses on delivering a short review concerning the current technologies, future perspectives, and the evaluation of some use cased associated with the analysis of big data.
The document discusses the concept of the Internet of Things (IoT), which involves connecting machines, facilities, fleets, networks, and people to sensors and controls. It notes that:
- The IoT has the potential to revolutionize how we live and do business across many industries.
- While the concept has been around since the 1990s, improving sensors, analytics, and declining costs are driving new applications in areas like automotive, healthcare, manufacturing and more.
- Companies face challenges in developing IoT strategies, integrating technologies, managing and analyzing sensor data at scale, and ensuring security and privacy.
How smart, connected products are transforming companies presentation (edit...Fahmy Amrillah
Information technology is revolutionizing products. Once composed solely of mechanical and electrical parts, products have become complex systems that combine hardware, sensors, data storage, microprocessors, software, and connectivity in myriad ways. These “smart, connected products”—made possible by vast improvements in processing power and device miniaturization and by the network benefits of ubiquitous wireless connectivity—have unleashed a new era of competition.
by Michael E. Porter and James E. Heppelmann
The document discusses applications of cyber-physical systems and robotics. Some key areas discussed include smart manufacturing using robotics working safely with humans, transportation systems using vehicle-to-vehicle communication and autonomous vehicles, smart energy grids, infrastructure monitoring using sensors, and medical devices. The integration of computation, networking, and physical processes allows innovative applications that can improve efficiency, safety, reliability and sustainability across many sectors.
The expansion of the Internet of Things IoT implies progressively dynamic client gadgets on the Internet. IoT devices can be ordinary articles from vehicles, advanced mobile phones to wearable sensors. Huge measures of information are produced by IoT devices through the assortment and transmission of information required for the yield of valuable results and in this way, an ef cient approach to work is significant. In the public eye today, mobile communication and mobile computing play a critical job in each part of our lives, both individual and open correspondence. By utilizing Cloud Computing with IoT, data computations are situated outside the devices henceforth diminishing the strain on the devices themselves. IoT devices are additionally frequently portable and with versatility comes the need to have wireless connections to the cloud. Therefore, Mobile Cloud Computing MCC gets appropriate. However, the development in mobile computing use can be improved by coordinating portable figuring into distributed computing. This will bring about developing another model called Mobile Cloud Computing MCC that has as of late pulled in a lot of consideration in the academic sector. This paper investigates its features, advantages, applications, and difficulties of Mobile Cloud Computing. Research endeavours towards the execution of Mobile Computing are additionally talked about giving an understanding of the fate of the innovation. Sujay Sudhakar Parkhe "Smart Computing: Mobile + Cloud" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30340.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/30340/smart-computing-mobile--cloud/sujay-sudhakar-parkhe
Study on Issues in Managing and Protecting Data of IOTijsrd.com
This paper discusses variety of issues for preserving and managing data produced by IoT. Every second large amount of data are added or updated in the IoT databases across the heterogeneous environment. While managing the data each phase of data processing for IoT data is exigent like storing data, querying, indexing, transaction management and failure handling. We also refer to the problem of data integration and protection as data requires to be fit in single layout and travel securely as they arrive in the pool from diversified sources in different structure. Finally, we confer a standardized pathway to manage and to defend data in consistent manner.
The document discusses Nepal's Network Readiness Index (NRI) rankings from 2013 to 2021. It provides details on what the NRI measures, including the four pillars of technology, people, governance, and impact. Nepal's NRI ranking has fluctuated between 99 and 126 in recent years. To improve its ranking, Nepal needs to focus on improving access to technology, encouraging local content creation, and preparing for future technologies. The pillars that Nepal scored lowest in were technology and people.
Key Trends and Opportunities in Business Mobility and Enterprise CommunicationsRaúl Castañón Martínez
Three key trends in 2011 are: 1) smartphones and tablets becoming more popular than PCs, 2) employees bringing their own devices to work (BYOD), and 3) consumer technology influencing enterprises. This poses challenges for IT like increasing costs and security risks. IT must consider factors like security, mobility needs, and company culture to determine the best approach. Options include company-owned devices, BYOD, or consumerization. If handled properly, embracing mobility and consumerization can boost productivity and lower costs for companies.
A Survey Report on : Security & Challenges in Internet of Thingsijsrd.com
In the era of computing technology, Internet of Things (IoT) devices are now popular in each and every domains like e-governance, e-Health, e-Home, e-Commerce, and e-Trafficking etc. Iot is spreading from small to large applications in all fields like Smart Cities, Smart Grids, Smart Transportation. As on one side IoT provide facilities and services for the society. On the other hand, IoT security is also a crucial issues.IoT security is an area which totally concerned for giving security to connected devices and networks in the IoT .As, IoT is vast area with usability, performance, security, and reliability as a major challenges in it. The growth of the IoT is exponentially increases as driven by market pressures, which proportionally increases the security threats involved in IoT The relationship between the security and billions of devices connecting to the Internet cannot be described with existing mathematical methods. In this paper, we explore the opportunities possible in the IoT with security threats and challenges associated with it.
Industrial internet big data german market studySari Ojala
The document provides a market evaluation report on business opportunities in data analytics software and related services in Germany. It discusses the scope, definitions, and structure of the report. Key topics covered include big data, IoT, industry 4.0, data analytics, vertical markets, customer readiness, the competitive environment, and use cases. The report aims to assess market entry opportunities with a focus on how German small and medium-sized businesses can leverage data to gain competitive advantages.
Most Significant Trends Impacting Global Supply Chain and Manufacturing Teamsbobferrari823
Within the next five years, five converging mega-trends will impact global supply chain and manufacturing teams. This presentation reviews these trends and offers conclusions as to their impact.
Insight into IoT Applications and Common Practice Challengesijtsrd
IoT caused a revolution in the technological world. Not only is the IoT related to computers, people or cell phones but also to various sensors, actuators, vehicles, and other modern appliances. There are around 14 billion interconnected digital devices across the globe i.e. almost 2 devices per human being on earth. The IoT serves as a medium to connect non living things to the internet to transfer information from one point to another in their community network which automates processes and ultimately makes the life of human beings convenient. The subsequent result of amalgamating internet connectivity with powerful data analysis is a complete change in the way we humans work and live. The most vital characteristics of IoT include connectivity, active engagement, sensors, artificial intelligence, and small device use. All of this creates many challenges that need to be solved to keep this technology to continue expanding. In this paper, we have identified various applications of IoT based on recent technological and business trends and highlighted the existing challenges faced by IoT which need to be addressed considering the exponential acceptance of the concept globally and the way those challenges had been addressed in the past. We have also made a few comments on the way such challenges are being attempted to be resolved now. This paper presents the current status Internet of Things IoT in terms of technical details, and applications. Also, this paper opens a window for future work on the historical approach to study and address IoT challenges. Lubna Alazzawi | Jamal Alotaibi "Insight into IoT Applications and Common Practice Challenges" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30286.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/30286/insight-into-iot-applications-and-common-practice-challenges/lubna-alazzawi
[GE207] Session03: Digital Technology TrendsSukanya Ben
This document discusses several emerging digital technology trends, including:
- Internet of Things (IoT) which connects devices like vehicles and appliances to exchange data over networks. IoT is expected to grow exponentially with an estimated 1 trillion connected devices by 2025.
- Big data and machine learning which analyze large and complex datasets to uncover insights. Popular applications include social media, mobile, and sensor data from IoT devices.
- Cloud computing which provides on-demand access to computing resources and data storage over the internet. Cloud services include Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS).
- Other trends discussed include artificial intelligence, robot
The Internet of Things (IoT), also referred to as the Internet of Objects, will change everything—including ourselves. This may seem like a bold statement, but consider the impact the Internet already had on education, science, communication, business, government, and humanity. Clearly, the Internet is one of the most important and a powerful creation in all of human history. This paper discussesIOT architecture, IOT applications and limitations of IOT.
The convergence of integrated software, efficient hardware and modern networking infrastructure has created a new technology environment. Industry 4.0 sits at the convergence of these technologies and enables many industries that we actively track. Catalyst Investors’ history in software and TMT is quite relevant to Industry 4.0. We are excited to meet and partner with growth stage companies that are built as Industry 4.0 solutions from the ground up, as well as existing service businesses that can adopt Industry 4.0 technologies as an evolution.
MIMOS Technologies Handbook provides overviews of MIMOS technologies in three sentences or less. The handbook is organized into key areas of data collection, data analytics and visualization, data infrastructure, and data protection. It provides one-page views of each technology that highlight their benefits. MIMOS focuses on developing data-centered technologies through research collaborations to help industries and businesses.
Definition, architecture, general applications, and energy management specified application of expert systems - Class presentation - University of Tabriz 2019
Analyzing Role of Big Data and IoT in Smart CitiesIJAEMSJORNAL
Big data and Internet of Things (IoT) technologies have evolved and expanded tremendously and hence play a major role in building feasible initiatives for smart city development. IoT and big data form a perfect blend in bringing an interesting and novel challenge to attain futuristic smart cities. These new challenges mainly focus on business and technology related issues that help smart cities to formulate their principles, vision, & requirements of smart city applications. In this paper, the role of big data and IoT technologies with respect to smart cities is analyzed. The benefits that smart cities will have from big data and IoT are also discussed. Various challenges faced by smart cities in general related to big data and IoT have also been described here. Moreover, the future statistics of IoT and big data with respect to smart cities is also deliberated.
The document discusses the future of the industry and production engineering in light of Industry 4.0. It describes the four industrial revolutions and technologies of Industry 4.0 like artificial intelligence, cloud computing, big data, cybersecurity and the internet of things. It emphasizes that the production engineer of the future will need skills in programming, robotics, data analysis as well as soft skills. The education system will need to adapt to prepare students for jobs working with intelligent machines through practices, personalized learning and real-world applicability.
Big Data has made it easier to gain loyal and happy customers in the utilities industry. It improves the ability of companies to quickly identify underlying issues and nip complaints in the bud.
Through big data analytics, utilities can improve customer experience, address changing demands, solve experience-related issues, manage grids more efficiently and gain full control of their resources. Read this paper to find out more.
Johannes Bauer, Director of the Quello Center at Michigan State University, covers various aspects of the digital economy including opportunities and challenges, technological and economic drivers, value creation in the digital economy, harnessing benefits and minimizing risks, and measuring the digital economy.
Due to availability of internet and evolution of embedded devices, Internet of things can be useful to contribute in energy domain. The Internet of Things (IoT) will deliver a smarter grid to enable more information and connectivity throughout the infrastructure and to homes. Through the IoT, consumers, manufacturers and utility providers will come across new ways to manage devices and ultimately conserve resources and save money by using smart meters, home gateways, smart plugs and connected appliances. The future smart home, various devices will be able to measure and share their energy consumption, and actively participate in house-wide or building wide energy management systems. This paper discusses the different approaches being taken worldwide to connect the smart grid. Full system solutions can be developed by combining hardware and software to address some of the challenges in building a smarter and more connected smart grid.
In today’s emerging world of Internet, each and every thing is supposed to be in connected mode with the help of billions of smart devices. By connecting all the devises used in our day to day life, make our life trouble less and easy. We are incorporated in a world where we are used to have smart phones, smart cars, smart gadgets, smart homes and smart cities. Different institutes and researchers are working for creating a smart world for us but real question which we need to emphasis on is how to make dumb devises talk with uncommon hardware and communication technology. For the same what kind of mechanism to use with various protocols and less human interaction. The purpose is to provide the key area for application of IoT and a platform on which various devices having different mechanism and protocols can communicate with an integrated architecture.
International Journal of Information Technologies & Intelligent Information Systems(ITI)is a bi-monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Software Engineering & Applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts & establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of software engineering & applications.
This document discusses the basics of operating smart buildings using IoT to improve flexibility and intelligence. It covers combining IoT functions and solutions in building operation, utilizing IoT capabilities across building functionalities, and use cases that demonstrate added flexibility for increased intelligence. Some key points include leveraging IoT data across functions can improve efficiency, flexibility, and services for occupants. Challenges include lack of standards, integration barriers, and security issues that must be addressed.
Designing for Manufacturing's 'Internet of Things'Cognizant
The deeper meshing of virtual and physical machines offers the potential to truly transform the manufacturing value chain, from suppliers through customers, and at every touchpoint along the way.
Study on Issues in Managing and Protecting Data of IOTijsrd.com
This paper discusses variety of issues for preserving and managing data produced by IoT. Every second large amount of data are added or updated in the IoT databases across the heterogeneous environment. While managing the data each phase of data processing for IoT data is exigent like storing data, querying, indexing, transaction management and failure handling. We also refer to the problem of data integration and protection as data requires to be fit in single layout and travel securely as they arrive in the pool from diversified sources in different structure. Finally, we confer a standardized pathway to manage and to defend data in consistent manner.
The document discusses Nepal's Network Readiness Index (NRI) rankings from 2013 to 2021. It provides details on what the NRI measures, including the four pillars of technology, people, governance, and impact. Nepal's NRI ranking has fluctuated between 99 and 126 in recent years. To improve its ranking, Nepal needs to focus on improving access to technology, encouraging local content creation, and preparing for future technologies. The pillars that Nepal scored lowest in were technology and people.
Key Trends and Opportunities in Business Mobility and Enterprise CommunicationsRaúl Castañón Martínez
Three key trends in 2011 are: 1) smartphones and tablets becoming more popular than PCs, 2) employees bringing their own devices to work (BYOD), and 3) consumer technology influencing enterprises. This poses challenges for IT like increasing costs and security risks. IT must consider factors like security, mobility needs, and company culture to determine the best approach. Options include company-owned devices, BYOD, or consumerization. If handled properly, embracing mobility and consumerization can boost productivity and lower costs for companies.
A Survey Report on : Security & Challenges in Internet of Thingsijsrd.com
In the era of computing technology, Internet of Things (IoT) devices are now popular in each and every domains like e-governance, e-Health, e-Home, e-Commerce, and e-Trafficking etc. Iot is spreading from small to large applications in all fields like Smart Cities, Smart Grids, Smart Transportation. As on one side IoT provide facilities and services for the society. On the other hand, IoT security is also a crucial issues.IoT security is an area which totally concerned for giving security to connected devices and networks in the IoT .As, IoT is vast area with usability, performance, security, and reliability as a major challenges in it. The growth of the IoT is exponentially increases as driven by market pressures, which proportionally increases the security threats involved in IoT The relationship between the security and billions of devices connecting to the Internet cannot be described with existing mathematical methods. In this paper, we explore the opportunities possible in the IoT with security threats and challenges associated with it.
Industrial internet big data german market studySari Ojala
The document provides a market evaluation report on business opportunities in data analytics software and related services in Germany. It discusses the scope, definitions, and structure of the report. Key topics covered include big data, IoT, industry 4.0, data analytics, vertical markets, customer readiness, the competitive environment, and use cases. The report aims to assess market entry opportunities with a focus on how German small and medium-sized businesses can leverage data to gain competitive advantages.
Most Significant Trends Impacting Global Supply Chain and Manufacturing Teamsbobferrari823
Within the next five years, five converging mega-trends will impact global supply chain and manufacturing teams. This presentation reviews these trends and offers conclusions as to their impact.
Insight into IoT Applications and Common Practice Challengesijtsrd
IoT caused a revolution in the technological world. Not only is the IoT related to computers, people or cell phones but also to various sensors, actuators, vehicles, and other modern appliances. There are around 14 billion interconnected digital devices across the globe i.e. almost 2 devices per human being on earth. The IoT serves as a medium to connect non living things to the internet to transfer information from one point to another in their community network which automates processes and ultimately makes the life of human beings convenient. The subsequent result of amalgamating internet connectivity with powerful data analysis is a complete change in the way we humans work and live. The most vital characteristics of IoT include connectivity, active engagement, sensors, artificial intelligence, and small device use. All of this creates many challenges that need to be solved to keep this technology to continue expanding. In this paper, we have identified various applications of IoT based on recent technological and business trends and highlighted the existing challenges faced by IoT which need to be addressed considering the exponential acceptance of the concept globally and the way those challenges had been addressed in the past. We have also made a few comments on the way such challenges are being attempted to be resolved now. This paper presents the current status Internet of Things IoT in terms of technical details, and applications. Also, this paper opens a window for future work on the historical approach to study and address IoT challenges. Lubna Alazzawi | Jamal Alotaibi "Insight into IoT Applications and Common Practice Challenges" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30286.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/30286/insight-into-iot-applications-and-common-practice-challenges/lubna-alazzawi
[GE207] Session03: Digital Technology TrendsSukanya Ben
This document discusses several emerging digital technology trends, including:
- Internet of Things (IoT) which connects devices like vehicles and appliances to exchange data over networks. IoT is expected to grow exponentially with an estimated 1 trillion connected devices by 2025.
- Big data and machine learning which analyze large and complex datasets to uncover insights. Popular applications include social media, mobile, and sensor data from IoT devices.
- Cloud computing which provides on-demand access to computing resources and data storage over the internet. Cloud services include Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS).
- Other trends discussed include artificial intelligence, robot
The Internet of Things (IoT), also referred to as the Internet of Objects, will change everything—including ourselves. This may seem like a bold statement, but consider the impact the Internet already had on education, science, communication, business, government, and humanity. Clearly, the Internet is one of the most important and a powerful creation in all of human history. This paper discussesIOT architecture, IOT applications and limitations of IOT.
The convergence of integrated software, efficient hardware and modern networking infrastructure has created a new technology environment. Industry 4.0 sits at the convergence of these technologies and enables many industries that we actively track. Catalyst Investors’ history in software and TMT is quite relevant to Industry 4.0. We are excited to meet and partner with growth stage companies that are built as Industry 4.0 solutions from the ground up, as well as existing service businesses that can adopt Industry 4.0 technologies as an evolution.
MIMOS Technologies Handbook provides overviews of MIMOS technologies in three sentences or less. The handbook is organized into key areas of data collection, data analytics and visualization, data infrastructure, and data protection. It provides one-page views of each technology that highlight their benefits. MIMOS focuses on developing data-centered technologies through research collaborations to help industries and businesses.
Definition, architecture, general applications, and energy management specified application of expert systems - Class presentation - University of Tabriz 2019
Analyzing Role of Big Data and IoT in Smart CitiesIJAEMSJORNAL
Big data and Internet of Things (IoT) technologies have evolved and expanded tremendously and hence play a major role in building feasible initiatives for smart city development. IoT and big data form a perfect blend in bringing an interesting and novel challenge to attain futuristic smart cities. These new challenges mainly focus on business and technology related issues that help smart cities to formulate their principles, vision, & requirements of smart city applications. In this paper, the role of big data and IoT technologies with respect to smart cities is analyzed. The benefits that smart cities will have from big data and IoT are also discussed. Various challenges faced by smart cities in general related to big data and IoT have also been described here. Moreover, the future statistics of IoT and big data with respect to smart cities is also deliberated.
The document discusses the future of the industry and production engineering in light of Industry 4.0. It describes the four industrial revolutions and technologies of Industry 4.0 like artificial intelligence, cloud computing, big data, cybersecurity and the internet of things. It emphasizes that the production engineer of the future will need skills in programming, robotics, data analysis as well as soft skills. The education system will need to adapt to prepare students for jobs working with intelligent machines through practices, personalized learning and real-world applicability.
Big Data has made it easier to gain loyal and happy customers in the utilities industry. It improves the ability of companies to quickly identify underlying issues and nip complaints in the bud.
Through big data analytics, utilities can improve customer experience, address changing demands, solve experience-related issues, manage grids more efficiently and gain full control of their resources. Read this paper to find out more.
Johannes Bauer, Director of the Quello Center at Michigan State University, covers various aspects of the digital economy including opportunities and challenges, technological and economic drivers, value creation in the digital economy, harnessing benefits and minimizing risks, and measuring the digital economy.
Due to availability of internet and evolution of embedded devices, Internet of things can be useful to contribute in energy domain. The Internet of Things (IoT) will deliver a smarter grid to enable more information and connectivity throughout the infrastructure and to homes. Through the IoT, consumers, manufacturers and utility providers will come across new ways to manage devices and ultimately conserve resources and save money by using smart meters, home gateways, smart plugs and connected appliances. The future smart home, various devices will be able to measure and share their energy consumption, and actively participate in house-wide or building wide energy management systems. This paper discusses the different approaches being taken worldwide to connect the smart grid. Full system solutions can be developed by combining hardware and software to address some of the challenges in building a smarter and more connected smart grid.
In today’s emerging world of Internet, each and every thing is supposed to be in connected mode with the help of billions of smart devices. By connecting all the devises used in our day to day life, make our life trouble less and easy. We are incorporated in a world where we are used to have smart phones, smart cars, smart gadgets, smart homes and smart cities. Different institutes and researchers are working for creating a smart world for us but real question which we need to emphasis on is how to make dumb devises talk with uncommon hardware and communication technology. For the same what kind of mechanism to use with various protocols and less human interaction. The purpose is to provide the key area for application of IoT and a platform on which various devices having different mechanism and protocols can communicate with an integrated architecture.
International Journal of Information Technologies & Intelligent Information Systems(ITI)is a bi-monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Software Engineering & Applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts & establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of software engineering & applications.
This document discusses the basics of operating smart buildings using IoT to improve flexibility and intelligence. It covers combining IoT functions and solutions in building operation, utilizing IoT capabilities across building functionalities, and use cases that demonstrate added flexibility for increased intelligence. Some key points include leveraging IoT data across functions can improve efficiency, flexibility, and services for occupants. Challenges include lack of standards, integration barriers, and security issues that must be addressed.
Designing for Manufacturing's 'Internet of Things'Cognizant
The deeper meshing of virtual and physical machines offers the potential to truly transform the manufacturing value chain, from suppliers through customers, and at every touchpoint along the way.
An Analysis of the Architecture of the Internet of Things.pdfCIOWomenMagazine
As we all know internet of things is a system of interrelated and inter-connected objects. These objects are able to collect and transfer data via a wireless network without any human intervention.
The document discusses digital transformation, Industry 4.0, and the Internet of Things. It defines Industry 4.0 as the current trend of automation and data exchange in manufacturing technologies. Industry 4.0 focuses on production processes within smart factories, while the Internet of Things focuses on the utilization of connected devices. The document also introduces concepts like cyber-physical systems, smart engineering, and smart factories, and discusses how they relate to digital transformation and each other.
The Internet of Things: P&C Carriers & the Power of DigitalCognizant
The document discusses how the growing Internet of Things can impact property and casualty insurance carriers. It states that IoT sensors collecting data from connected devices can help carriers improve underwriting, pricing, risk management, loss prevention, claims handling, and customer retention. Specifically, IoT data allows carriers to better assess risk exposures, prevent losses through remote monitoring, develop new insurance products tailored to industries and risks, and create a more personalized customer experience across the entire insurance lifecycle.
White Paper - Delivering on the IoT Experience - The HPE Universal IoT Platfo...Gary Wood
The document provides an overview of the HPE Universal IoT Platform, which is designed to address long-term IoT requirements. It allows for connection and information exchange between heterogeneous IoT devices and applications. The platform reduces dependency on legacy silo solutions and simplifies integrating diverse devices. It provides federation for device and service management and data acquisition/exposure. Key modules include device and service management, network interworking proxy, data acquisition and verification, data analytics, OSS/BSS, and data service cloud. The platform aims to enable monetization of IoT-generated data through delivering value to enterprise applications.
Definition, timeline, implemented technologies, requirements and comparison between different technologies of Internet of Things (IoT) in energy management, plus a regional comparison of IoT market size focusing on Iran.
Reaping the Benefits of the Internet of ThingsCognizant
Before they can realize the potential of the Internet of Things, organizations must deal with shortcomings in IT standards, skill sets, and data and infrastructure management capabilities.
SEMANTIC TECHNIQUES FOR IOT DATA AND SERVICE MANAGEMENT: ONTOSMART SYSTEMijwmn
In 2020 more than50 billions devices will be connected over the Internet. Every device will be connected to
anything, anyone, anytime and anywhere in the world of Internet of Thing or IoT. This network will
generate tremendous unstructured or semi structured data that should be shared between different
devices/machines for advanced and automated service delivery in the benefits of the user’s daily life. Thus,
mechanisms for data interoperability and automatic service discovery and delivery should be offered.
Although many approaches have been suggested in the state of art, none of these researches provide a fully
interoperable, light, flexible and modular Sensing/Actuating as service architecture. Therefore, this paper
introduces a new Semantic Multi Agent architecture named OntoSmart for IoT data and service
management through service oriented paradigm. It proposes sensors/actuators and scenarios independent
flexible context aware and distributed architecture for IoT systems, in particular smart home systems.
SEMANTIC TECHNIQUES FOR IOT DATA AND SERVICE MANAGEMENT: ONTOSMART SYSTEMijwmn
In 2020 more than50 billions devices will be connected over the Internet. Every device will be connected to
anything, anyone, anytime and anywhere in the world of Internet of Thing or IoT. This network will
generate tremendous unstructured or semi structured data that should be shared between different
devices/machines for advanced and automated service delivery in the benefits of the user’s daily life. Thus,
mechanisms for data interoperability and automatic service discovery and delivery should be offered.
Although many approaches have been suggested in the state of art, none of these researches provide a fully
interoperable, light, flexible and modular Sensing/Actuating as service architecture. Therefore, this paper
introduces a new Semantic Multi Agent architecture named OntoSmart for IoT data and service
management through service oriented paradigm. It proposes sensors/actuators and scenarios independent
flexible context aware and distributed architecture for IoT systems, in particular smart home systems.
SEMANTIC TECHNIQUES FOR IOT DATA AND SERVICE MANAGEMENT: ONTOSMART SYSTEMijwmn
In 2020 more than50 billions devices will be connected over the Internet. Every device will be connected to
anything, anyone, anytime and anywhere in the world of Internet of Thing or IoT. This network will
generate tremendous unstructured or semi structured data that should be shared between different
devices/machines for advanced and automated service delivery in the benefits of the user’s daily life. Thus,
mechanisms for data interoperability and automatic service discovery and delivery should be offered.
Although many approaches have been suggested in the state of art, none of these researches provide a fully
interoperable, light, flexible and modular Sensing/Actuating as service architecture. Therefore, this paper
introduces a new Semantic Multi Agent architecture named OntoSmart for IoT data and service
management through service oriented paradigm. It proposes sensors/actuators and scenarios independent
flexible context aware and distributed architecture for IoT systems, in particular smart home systems.
The document discusses the Internet of Things (IoT), which refers to a global network of machines and devices that can interact with each other. It identifies five essential IoT technologies - radio frequency identification, wireless sensor networks, middleware, cloud computing, and IoT application software. It also examines three categories of enterprise IoT applications - monitoring and control, big data and business analytics, and information sharing and collaboration. Finally, it discusses challenges of IoT implementation including data management, privacy, security, and integration complexity.
The document discusses smart manufacturing and its key enablers. It describes how smart manufacturing utilizes technologies like big data analysis, industrial IoT, blockchain, robotics, and digital twins to optimize manufacturing processes. A smart factory is presented as the vision of highly automated production facilitated by cyber-physical systems and the exchange of digital information. The advantages of smart manufacturing include increased productivity and efficiency through predictive maintenance and flexibility, while the main disadvantage is the upfront cost of implementation.
The software development sector is constantly expanding, creating a plethora of opportunities for organizations, startups, and entrepreneurs. We provide valuable information that helps you in software development for your business.
The document discusses how enterprise networks are facing increasing demands and complexity due to the growing variety of devices accessing them, including smartphones, tablets, and machine-to-machine devices. This poses challenges for CIOs in managing network traffic and costs. However, an intelligent network that can adapt to users' needs can help CIOs satisfy users while focusing on innovation. Such a network is described as being able to distribute content efficiently, enable application development, and anticipate future business requirements. This could allow the CIO to take on more strategic roles rather than getting bogged down in projects.
Get more information about software development. We are providing the best information which helps you to develop customized software for your business.
In this presentation, Mukta introduces IoT and associated trends. Mukta is interested in IoT applications in healthcare, she talks about reports on BP and breathing habits to help users in managing health.
This document contains information about Mukta V Satish, a 2nd year Computer Science and Engineering student at Dayanand Sagar College of Engineering in Bangalore. It provides an introduction to the Internet of Things (IoT) which connects everyday devices to the network to increase efficiency and enable new services. Some key trends in IoT discussed are the Web of Things, improving industrial applications through real-time monitoring, secure cloud analytics using elastic computing, and machine-generated responses. The document also outlines Mukta's interests in cloud analytics and developing an application to monitor health vitals using wearables.
Connecting Physical and Digital Worlds to Power the Industrial IoTCognizant
The Industrial Internet of Things (IIoT) merges enterprise IT and manufacturing operations technologies by making optimal use of IoT sensor data, analytics, cloud, process automaiton software and more. The payoffs: increased efficiency, lower operating costs, reduced disruptions, improved productivity and higher margins.
Process oriented architecture for digital transformation 2015Vinay Mummigatti
How the digitally savvy enterprises need to transform their business processes - A paper on architecture and patterns for business and technology audience.
Similar to Connected Products for the Industrial World (20)
Using Adaptive Scrum to Tame Process Reverse Engineering in Data Analytics Pr...Cognizant
Organizations rely on analytics to make intelligent decisions and improve business performance, which sometimes requires reproducing business processes from a legacy application to a digital-native state to reduce the functional, technical and operational debts. Adaptive Scrum can reduce the complexity of the reproduction process iteratively as well as provide transparency in data analytics porojects.
Data Modernization: Breaking the AI Vicious Cycle for Superior Decision-makingCognizant
The document discusses how most companies are not fully leveraging artificial intelligence (AI) and data for decision-making. It finds that only 20% of companies are "leaders" in using AI for decisions, while the remaining 80% are stuck in a "vicious cycle" of not understanding AI's potential, having low trust in AI, and limited adoption. Leaders use more sophisticated verification of AI decisions and a wider range of AI technologies beyond chatbots. The document provides recommendations for breaking the vicious cycle, including appointing AI champions, starting with specific high-impact decisions, and institutionalizing continuous learning about AI advances.
It Takes an Ecosystem: How Technology Companies Deliver Exceptional ExperiencesCognizant
Experience is becoming a key strategy for technology companies as they shift to cloud-based subscription models. This requires building an "experience ecosystem" that breaks down silos and involves partners. Building such an ecosystem involves adopting a cross-functional approach to experience, making experience data-driven to generate insights, and creating platforms to enable connected selling between companies and partners.
Intuition is not a mystery but rather a mechanistic process based on accumulated experience. Leading businesses are engineering intuition into their organizations by harnessing machine learning software, massive cloud processing power, huge amounts of data, and design thinking in experiences. This allows them to anticipate and act with speed and insight, improving decision making through data-driven insights and acting as if on intuition.
The Work Ahead: Transportation and Logistics Delivering on the Digital-Physic...Cognizant
The T&L industry appears poised to accelerate its long-overdue modernization drive, as the pandemic spurs an increased need for agility and resilience, according to our study.
Enhancing Desirability: Five Considerations for Winning Digital InitiativesCognizant
To be a modern digital business in the post-COVID era, organizations must be fanatical about the experiences they deliver to an increasingly savvy and expectant user community. Getting there requires a mastery of human-design thinking, compelling user interface and interaction design, and a focus on functional and nonfunctional capabilities that drive business differentiation and results.
The Work Ahead in Manufacturing: Fulfilling the Agility MandateCognizant
Manufacturers are ahead of other industries in IoT deployments but lag in investments in analytics and AI needed to maximize IoT's benefits. While many have IoT pilots, few have implemented machine learning at scale to analyze sensor data and optimize processes. To fully digitize manufacturing, investments in automation, analytics, and AI must increase from the current 5.5% of revenue to over 11% to integrate IT, OT, and PT across the value chain.
The Work Ahead in Higher Education: Repaving the Road for the Employees of To...Cognizant
Higher-ed institutions expect pandemic-driven disruption to continue, especially as hyperconnectivity, analytics and AI drive personalized education models over the lifetime of the learner, according to our recent research.
Engineering the Next-Gen Digital Claims Organisation for Australian General I...Cognizant
The document discusses potential future states for the claims organization of Australian general insurers. It notes that gradual changes like increasing climate volatility, new technologies, and changing customer demographics will reshape the insurance industry and claims processes. Five potential end states for claims organizations are described: 1) traditional claims will demand faster processing; 2) a larger percentage of claims will come from new digital risks; 3) claims processes may become "Uberized" through partnerships; 4) claims organizations will face challenges in risk management propositions; 5) humans and machines will work together to adjudicate claims using large data and computing power. The document argues that insurers must transform claims through digital technologies to concurrently improve customer experience, operational effectiveness, and efficiencies
Profitability in the Direct-to-Consumer Marketplace: A Playbook for Media and...Cognizant
Amid constant change, industry leaders need an upgraded IT infrastructure capable of adapting to audience expectations while proactively anticipating ever-evolving business requirements.
Green Rush: The Economic Imperative for SustainabilityCognizant
Green business is good business, according to our recent research, whether for companies monetizing tech tools used for sustainability or for those that see the impact of these initiatives on business goals.
Policy Administration Modernization: Four Paths for InsurersCognizant
The pivot to digital is fraught with numerous obstacles but with proper planning and execution, legacy carriers can update their core systems and keep pace with the competition, while proactively addressing customer needs.
The Work Ahead in Utilities: Powering a Sustainable Future with DigitalCognizant
Utilities are starting to adopt digital technologies to eliminate slow processes, elevate customer experience and boost sustainability, according to our recent study.
AI in Media & Entertainment: Starting the Journey to ValueCognizant
Up to now, the global media & entertainment industry (M&E) has been lagging most other sectors in its adoption of artificial intelligence (AI). But our research shows that M&E companies are set to close the gap over the coming three years, as they ramp up their investments in AI and reap rising returns. The first steps? Getting a firm grip on data – the foundation of any successful AI strategy – and balancing technology spend with investments in AI skills.
Operations Workforce Management: A Data-Informed, Digital-First ApproachCognizant
As #WorkFromAnywhere becomes the rule rather than the exception, organizations face an important question: How can they increase their digital quotient to engage and enable a remote operations workforce to work collaboratively to deliver onclient requirements and contractual commitments?
Five Priorities for Quality Engineering When Taking Banking to the CloudCognizant
As banks move to cloud-based banking platforms for lower costs and greater agility, they must seamlessly integrate technologies and workflows while ensuring security, performance and an enhanced user experience. Here are five ways cloud-focused quality assurance helps banks maximize the benefits.
Getting Ahead With AI: How APAC Companies Replicate Success by Remaining FocusedCognizant
Changing market dynamics are propelling Asia-Pacific businesses to take a highly disciplined and focused approach to ensuring that their AI initiatives rapidly scale and quickly generate heightened business impact.
The Work Ahead in Intelligent Automation: Coping with Complexity in a Post-Pa...Cognizant
Intelligent automation continues to be a top driver of the future of work, according to our recent study. To reap the full advantages, businesses need to move from isolated to widespread deployment.
The Work Ahead in Intelligent Automation: Coping with Complexity in a Post-Pa...
Connected Products for the Industrial World
1. Connected Products for
the Industrial World
By leveraging product-centric connected ecosystems,
manufacturers can create new and more effective business
models, advance operational excellence, and design and
develop better products and services that align with customer
needs and preferences.
3. CONNECTED PRODUCTS FOR THE INDUSTRIAL WORLD 3
Executive Summary
The Internet of Things (IoT) is getting a lot of attention from the industrial sector,
particularly with advances in information and communications technology (ICT),
the cross-pollination of talent in business, IT and consulting across industry
sectors, and the growth of the knowledge economy. Devices instrumented to
collect and transmit intelligence on user behavior and environmental conditions
over IP networks have created vast opportunities to build connected ecosystems
surrounding industrial products.
BasedonarecentstudybyCognizant’sCenterfortheFutureofWork,thebusiness-
to-business industrial equipment space is among the most active areas for smart
product development, with 58% of respondents saying their companies are
already developing products. Smart packaging and consumer home devices are
next, at 57% and 40%, respectively.
1
Multiple industries are adopting different
forms of connected solutions, with varying degrees of success. Although the
opportunities and risks of these solutions are unique to each industry’s priorities
and the business context, common underlying elements run across all of these
connected initiatives.
This white paper explores the opportunities and challenges for organizations that
want to adopt product-centric ecosystems, or what we call connected ecosystems.
These ecosystems create business value by leveraging data value chains built
around the concept of Code Halo™ thinking.
2
In this context, meaning is derived
and applied from the intersection of data generated by smart products, devices,
processes, organizations, employees and consumers. Although this whitepaper is
aimedatindustrialapplicationsincoresectorssuchasmanufacturingandutilities,
it also illustrates examples covering the industrial and consumer segments.
4. 4 KEEP CHALLENGING August 2015
Connected Ecosystems and Products
Technology is driving change, as seen in the areas of sensorization,3
power
management, connectivity, computing and interactive technologies (including visu-
alization). Most connected ecosystems consist of four major elements (see Figure 1):
• Hardware: Hardware includes any device or system with some behavioral func-
tionality and the ability to generate and transmit data. If the device is incapable
of communicating, capabilities must be added to permit it to share data within
a connected ecosystem. A low-power industrial motor with no local computing
or communication capability is an example of a passive device that can become
active (or smart) with the addition of a vibration-monitoring sensor with the
ability to transmit data. At a broad level, the degree of device “smartness” is
dependent on its sensory, data gathering, storage, local computing, decision-
making and interaction capabilities. The best example of active hardware is the
smartphone, with its built-in computing and communication capabilities, which
can quickly be onboarded to an IP network.
Depending on the context, a device or product could be a sensor, a piece of heavy
equipment or machinery, or a car (see Figure 2, next page).
Hardware
Consumer
Data Management
• Ability to manage 360-degree
view of data
• In-memory databases
• Improved storage capacity
• Ever-reducing chip sizes
Traditional + Big Data
Network
• Pervasive connectivity
• Lightweight protocols
• Interoperability
• Security mechanisms Wired + Wireless
Industrial
Intelligence & Interaction
• Evolving analytics tools ecosystem
• Improvements in computing
• Multi-echelon intelligence
• Advanced interactive technologies
Central/Distributed
Interaction
ADVANCEMENTS
• Advancement in material sciences
• Miniaturization
• Reduced cost of embedded products
• Reduced form factor
• Better power management
Anatomy of a Connected Ecosystem
Figure 1
5. CONNECTED PRODUCTS FOR THE INDUSTRIAL WORLD 5
• Network: Networks are pervasive, thanks to ever increasing advances in
hardware footprint, open standards, interoperability and available bandwidth.
Many wireless networks, such as 802.11, Bluetooth and Zigbee, are available in
the consumer space, whereas commercial enterprises rely primarily on wired
networks, such as Modbus, FFB,4
and HART.5
Over the last decade, industrial
organizations have begun moving away from wired networks to reduce the miles
of wires running across their plants, as well as ease of installation and mainte-
nance. The industrial world was the first to embrace the machine-to-machine
(M2M) phenomenon decades ago, and today’s IoT is a consumerized version of
that. The scalability of a connected ecosystem within an enterprise and across an
ecosystem is dependent on the network and data management strategy.
• Data management: Industrial companies have a long history of managing
machine data related to their people (usage), processes and products. The pro-
liferation of IT systems is generating a huge repository of data, with multiple
software applications creating data silos on the back end. Many companies are
now trying to create connections between these silos to reflect the single version
of a “true” state. There is also a movement away from traditional relational
databases to big data-oriented and in-memory databases to store, analyze
and make meaning of various data types (structured, unstructured and semi-
structured). Consumers also struggle to manage their personal data in their
Industrial: A B2B segment that
includes devices in both industrial and
business environments. Examples
include a pressure sensor, a turbine or
a packaging machine.
Consumer: A B2C segment, with
devices in the consumer space,
such as smartphones, cars,
washing machines, televisions.
Sensor Enablement
Analog, digital temp,
pressure, motion, etc.
Device Connectivity
Wireless (ZigBee,
Bluetooth),
wired (ModBus,
CanBus)
Device Management
Hardware, firmware,
diagnostics
Intelligence &
Decision-Making
Local rules processing
Behavioral
Modeling
DEVICE
Social: A consumer-to-consumer (C2C)
segment, in which products are being
developed and consumed by consum-
ers only. Examples include 3-D printed
and crowdsourced products.
DEVICE CONTEXT
INDUSTRIAL
CONSUMER
SOCIAL
The Broad Swath of Smart Hardware
Figure 2
6. 6 KEEP CHALLENGING August 2015
everyday lives (digital images, music, application software, etc.). With the advent
of the smart product economy, businesses must develop the ability to manage
the scale and security of data. Both in the consumer and industrial contexts, the
data management strategy will dictate the success of a connected ecosystem.
• Intelligence and user interaction: Visualization is the first stage of contextual-
ized intelligence, while artificial intelligence-based decision systems are the last.
Multiple software applications are available to address the needs of both visual-
ization and business intelligence. Analytical and statistical tools such as R, Matlab,
SPSS and SAS are commonly used for simulation, modeling and optimization,
and for creating algorithms to address different types of intelligence require-
ments, but no single tool is a fit across different business contexts. The challenge
lies in selecting the right tools or creating an overarching tools ecosystem with
common data access and integration layers. Such solutions are evolving, as orga-
nizations establish dedicated data labs to generate insights into their business,
ranging from product design and manufacturing to after-sales services.
Device Code Halos and the Four
Dimensions of Business Value
Across industries, the lifecycles of products, manu-
facturing assets and fulfillment are tightly coupled,
generating various forms of data when active (smart)
devices across these lifecycles interact within a
connected ecosystem. Such data typically contains
a multitude of information regarding product design,
process, usage, operating environment, mainte-
nance history and customer preferences, along with
resource consumption. We call this swirling field of
data (real-time or historical) a device Code Halo.
With devices at the center of the connected
ecosystems, the resulting Code Halos act as the seeds
of the data value chain (DVC). A connected ecosystem
based on smartly designed DVCs can help businesses
derive value along four dimensions (see Figure 3):
Operational Improvement
Operational improvement — one of the most common
value dimensions — includes opportunities that
address the traditional goals of cheaper, better and
faster, with the objective of creating highly efficient
operations and processes. Large distributed-asset-
based industries, such as rail and utilities, are moving
toward integrated proactive asset management
frameworks, making use of the enhanced capabili-
ties of networking and centralized data processing. A
better understanding of asset condition and deterio-
ration, using both historical and operational data, will
bolster more proactive and predictive asset mainte-
nance and renewal, compared with today’s reactive/
fixed approach.
1
2
3
4
Operational Improvements
Addressing challenges in opera-
tions and processes faced in the
value chain, from product design
to delivery.
Product Innovation
Improvements in the design of
existing products and the creation
of new ones.
Customer Experience
(Product & Services)
Initiatives to provide personalized
experience to the customer for
both products and services.
New Business Models
Servitization of the existing
portfolio by leveraging
the connected ecosystem.
The Four Dimensions
of Business Value
Figure 3
7. CONNECTED PRODUCTS FOR THE INDUSTRIAL WORLD 7
In cold chain logistics, several factors — such as ambient conditions, product
metabolism and driving behavior (door opening/closing patterns, harsh driving),
controller tuning, loading conditions and vehicle health index — have a significant
impact on operational expenditures (e.g., fuel and maintenance), quality (e.g., tem-
perature variance) and service (e.g., SLA, quality on arrival). Such vehicles with
“digital” reefers (refrigeration unit) act as nodes on a network and help achieve fleet
and workforce effectiveness.
Other areas, such as facility management and infrastructure businesses (e.g.,
airports), are examining holistic ways to reduce operational costs beyond complying
with green regulations (noise, energy and carbon footprint) by optimizing around
processes and systems halos. To create an enhanced ecosystem, such solutions
must also extend data from external climatic conditions, internal ambient conditions,
available headroom, passenger preferences (through personal Code Halos) and
asset health and usage patterns.
Industrial OEMs are installing sensing gear to monitor the installed base of
equipment and maximize return on assets (RoA) by developing remote service
monitoring frameworks that overlay a set of monitoring, analytical and interven-
tion services. Such solutions enhance the serviceability and reliability of industrial
equipment, while reducing the total cost of ownership (TCO) of the assets.
Quick Take
Applying Code Halo Thinking to Oil
Exploration
We recently helped an oil and gas major improve its drilling
system. The improved system has enhanced drilling efficiency,
and reduced tool downtime by monitoring vibrations of the tool
string, and predicting failure of the drilling motor.
The system consumes surface data to analyze downhole perfor-
mance and develop a dynamic model to identify and segregate
harsh drilling spots. The system leverages data generated by
the interaction of the drilling system, drilling operator and
drilling column. The model takes into account drilling torque,
rotation per minute (RPM), differential pressure, hydrostatic
pressure, weight on bit (WoB), length of the drilling strings and
resonance frequency, among other factors to support smarter
operator decisions
As a result, the client expects to reduce drilling time by 5%,
totalling $1 million per year in savings per rig.
8. 8 KEEP CHALLENGING August 2015
Product Innovation
Capturing the voice of customers and businesses across the product lifecycle
can substantially help improve product design and performance. Companies can
enhance existing product designs by including or removing specific features,
tweaking designs if they can understand usage patterns, perform parts rationaliza-
tion and predict performance, etc.
Product Code Halos can help detect failure patterns at an early stage. Data-driven
models can predict the likelihood of component or product failure by capturing per-
formance degradation over time. Further, equipment manufacturers can track per-
formance of their installed products to develop meaningful insights about product
performance and failure events, leading to improved product design.
Pharmaceuticals companies are exploring frameworks that define the optimal
manufacturing process for new products (golden recipes, SOPs) by integrating data
from different phases, such as R&D, engineering, manufacturing and maintenance
to boost new product success. The objective is to analyze data to predict yield,
quality, deviation and process reliability to achieve seamless commercialization of
a drug or active product ingredient.
Customer Experience
Customer preference and personalization is becoming pivotal to market differ-
entiation and business success. From customized cars to customized healthcare,
businesses are leveraging technology to offer personalized products and services
to new-age demanding customers.
Creating a Personalized Car Experience
We are working with an auto OEM to develop a connected services
platform program that maps geographic requirements for model-
specific car features, drawing from more than 25 data sources.
This is critical because various nations have different regulatory
requirements. For example, Europe’s eCall, Russia’s ERA-GLONASS
and Brazil’s SIMRAV are among the regulations that require
vehicles to be fitted with emergency driver assistance systems.
Brazil’s Contran 245 mandate aims to reduce rampant vehicle
theft by requiring all vehicles to be fitted with a global position-
ing system. Other geography-specific features include teen driver
monitoring, visual and audio warnings, etc.
Quick Take
9. CONNECTED PRODUCTS FOR THE INDUSTRIAL WORLD 9
Auto OEMs are exploring ways to differentiate brands by creating mashups of data
from vehicle and infotainment, enterprise and social content to create uniquely
personalized customer experiences. Retailers and other businesses in the fashion
industry are among the earliest adopters of this approach, with certain customers
showing interest in creating their own apparel, as well as designing their own
shoes and accessories. Some retailers offer enhanced experiences that include
personalized advertising based on customer profiles and the products they are
looking at.
This type of customer engagement can be created by using a variety of digital
layouts, such as display boards, kiosks and smartphones. Brand owners can
monitor retail chain traffic using cameras and motion sensors to collect demo-
graphic information and dwelling time in various parts of the store to optimize
product placement and stocking patterns.
New Business Models
This dimension refers to “servitization”6
oppor-
tunities and new business models based on
connected products, in which businesses
create knowledge-based service offerings
around their existing product portfolio.
Fast-moving consumer goods (FMCG)
companies are exploring the ability to
exchange data with smart vending machines
fitted with embedded sensors that can com-
municate using 2G/3G/LTE networks (in turn
creating new revenue streams for telcos)
to supplement their existing revenues from
the vending network. These companies also expect to earn additional revenues
through digital signage and third-party coupons/vouchers. Smart machines can
exchange vending Code Halos in real-time, including the number and type of drinks
consumed, machine health, ambient conditions and heat leakage. Stakeholders
can develop meaningful insights from the machine operations, demand patterns
and impact of promotional campaigns. A proactive maintenance and spare parts
strategy could be effectively woven around an integrated network of devices.
Additionally, taxi cab businesses are leveraging dynamic pricing models to
maximize profits and improve operational efficiency (e.g., vehicle utilization). This
has been enabled by creating an ecosystem of devices and optimizing supply-
demand dynamics.
Smart metering in the utilities industry is another example where billing can be
optimized by evaluating usage patterns. Insurers are also experimenting with
usage-based insurance (UBI), configuring insurance premiums based on users’
driving patterns (personal Code Halo) and data collected from the automobile’s
telematics device. Popular UBI products, such as “manage how you drive” (MHYD)
and “pay as you drive” (PAYD), allow insurance companies to offer discounts to
customers based on their driving behaviors. Companies offer discounts of up to
30% based on driving behaviors, and customers can save 10% to 15% on their
premiums.7
MetroMile,8
a U.S.-based car insurance company, charges customers for
the actual miles driven, offering scalable pricing for both high- and low-frequency
drivers.
Smart machines can exchange
vending Code Halos in real-
time, including the number
and type of drinks consumed,
machine health, ambient
conditions and heat leakage.
10. 10 KEEP CHALLENGING August 2015
Challenges with Connected Ecosystems
All four of these dimensions present their fair share of challenges. Figure 4 maps
the most common challenges faced while exploring the opportunities available to a
given business value dimension, along with their severity.
Entitlement Management: Who Owns What?
A connected ecosystem creates a data value chain between a device and the intel-
ligent system. An entity (i.e., a company or individual) can own either a part or
the entirety of the DVC, depending on ecosystem factors such as the stakeholders,
business value and technology involved. A wearable device connected to an athlete
to monitor key parameters such as sweat and heartbeat is an example of a DVC
owned by an individual, who can determine what data to transmit, the transmis-
sion network (depending on the device), where to store the data and what kind of
decisions to be made.
Not all consumer-oriented ecosystems provide full control of the DVC to the end
customer. For example, in the communications space, multiple stakeholders, such as
smartphone manufacturers and app developers, own most of the DVC. These stake-
holders also own the data management (gathered from thousands of devices sold),
and sometimes even have control over what data needs to be gathered from the
phone (ideally with the consumer’s consent), and generate intelligence based on
the gathered data. In contrast, a telecom carrier owns the network infrastructure,
along with data around network statistics, usage, diagnostics, etc.
A similar example is that of a “connected” vehicle, where an OEM manufacturers
the device (a car), and telecom carriers and app developers capture most of the
Connected Ecosystems: Opportunities, Challenges
Figure 4
New
Business
Model
Operational
Improvement
Customer
Experience
Product
Innovation
Creation of new knowledge-
based service lines and new
business models.
Business process improvement
to reduce the cost of creating
and serving offerings.
Customized products and
services to command premium
pricing and brand loyalty.
Capturing VOCs across the
product value chain to
improve/introduce features.
DIMENSIONS CHALLENGES
Challenge severity
Data
Entitlement
Monetization
Strategy
Security
& Privacy
Technology
Selection
11. CONNECTED PRODUCTS FOR THE INDUSTRIAL WORLD 11
user’s data, as well as manage it. Although auto OEMs see value in the captured
data, they don’t necessarily own the data. However, applications based on data
mashups from diverse sources can help auto OEMs create brand differentiation by
applying advanced analytics.
Market segmentation mapped to demographic needs can become the basis for
deciding on a new feature introduction program. However, data ownership coupled
with customer reluctance to pay an additional premium for these digital features
has stifled the potential of what can be achieved in terms of consumer profiling
and catering to the specifics. (To learn more, read our white papers “Exploring the
Connected Car” and “The New Auto Insurance Ecosystem: Telematics, Mobility and
the Connected Car.”)
For industrial applications, examples of partial
or full ownership of DVCs are emerging, in
which a machine or device is already installed at
a customer’s premises and functions in tandem
with upstream and downstream processes and
systems.
Industrial customers maintain strict control
over the data leaving their ecosystems, whether
it’s device data, process data or product
data, and they have varied requirements
for governance and security compliance. For example, a process control system
(provided by a third-party vendor) running in a refinery is a smart device that can
communicate on a network and make real-time decisions. The program running on
the control system (CS) is specific to the process and has a certain IP attached to it.
Thus, the CS handles both product and process data. Essentially, the refinery owns
the process data, the network and the data management, and it makes business
decisions based on the data. The CS vendor can plug into the refinery’s network
(not the plant network) and gather specific data to analyze the performance of the
CS (i.e., product data). The vendor can have limited access to the DVC.
Ownership of the DVC is a function of many parameters. Because ecosystem
designers must manage the entitlement of the data, ecosystem integration is key,
especially to create new business models and enhance the customer experience.
Monetization Strategy: Business Lags Behind the Technology
This is the most puzzling piece of the entire connected story. Technology advance-
ments have led to a plethora of devices, networks, data management systems
and software applications, creating opportunities for device interaction of many
types. As a result, businesses are looking to generate value from different interac-
tions, such as how a driver drives a vehicle, how a machinist uses a machine, how
a reefer’s performance impacts packaged product metabolism, etc. But imagine if
your microwave and refrigerator were sensorized, onboarded to a network and able
to speak with one another; should a customer pay more for these products, and if
so, how much more? Just two intelligent devices talking to each other is not enough
— context and understanding of customer value is key.
Industrial businesses are complementing their existing product portfolios with
solutions and services to generate greater value. As Figure 5 (next page) shows,
adoption of a connected ecosystem varies depending on where the products fit in
the product/services continuum. Leveraging a connected ecosystem to monetize
services and create new business models is especially challenging for the businesses
positioned on the extreme left of the product/service continuum. The movement
Just two intelligent devices
talking to each other is
not enough — context and
understanding of customer
value is key.
12. 12 KEEP CHALLENGING August 2015
toward the right side of the continuum (toward pure services) is what is known as
servitization.
Although the movement to the right is not new for many industries, connected
ecosystems have accelerated the trend. Servitization is here to stay, with new
business models evolving due to the following key factors:
• Opportunities for recurring revenues.
• Relatively low Cap-Ex.
• Shrinking margins for pure products.
However, it is still challenging to create new revenue models and services based on
a connected ecosystem. The reasons include:
• Evolving customer KPIs and needs:
>> It is difficult to make a case for tangible, sustainable advantage with the help
of a connected ecosystem. Customers are asking for specific recommenda-
tions around their businesses; mere reports and insights are not enough.
>> Customers want businesses to invest in and prove the case for connected
ecosystems. Output-based models are gaining in popularity, along with co-
investment; we see companies being willing to pay to participate in the eco-
system only if they see business value emanating from it.
• Lack of understanding of the product’s ecosystem in the installed base.
Product ecosystems can include both upstream and downstream processes and
systems, the environment in which the product operates, its overall impact on
the process, external factors that create process performance bottlenecks, the
workforce that manages and operates the product, the cost incurred by the cus-
tomer to procure the product, third-parties servicing the product, consumables
procured during normal operations, issues with configurations and settings, stan-
dard operating procedures followed while using the product, and the product’s
resource consumption. Gathering such data from the ecosystem is a significant
challenge, which makes the device’s “smartness” all the more critical.
Churning the Revenue Model
A connected ecosystem typically represents the following types of revenue oppor-
tunities (or a combination thereof):
PURE PRODUCTS SOLUTIONS PURE SERVICES
Industry Examples:
Component manufacturers,
textile, pulp & paper, metals
& mining, etc.
Linear margins,
commoditized products
Viable servitization zone
(for industrial segment)
Not applicable
to core industries
Non-linear margins,
differentiation via solutions
Varied, difficult to
differentiate
Industry Examples:
Automotive, consumer goods,
industrial, etc.
Industry Examples:
Engineering services,
consulting
VALUE
Rationalizing the Product/Service Continuum
Figure5
13. CONNECTED PRODUCTS FOR THE INDUSTRIAL WORLD 13
• Traditional product revenue: Premium pricing for the smart product.
• Service-based revenue: Revenue driven by services around the products and
pure services. This can include knowledge-based service revenue (advisory
services, reports, data as a service), dynamic pricing models and usage-based
models.
• Product usage-based/leasing models: Unit pricing (per pound, per pack, per
hour, etc.).
Designing a win-win business model requires significant collaborative efforts with
clients and business partners. Successful revenue models often involve co-invest-
ment and co-piloting with customers.
As Figure 6 reveals, the aim is to realize any of the aforementioned revenue types
by reaching the prescribed state. A major challenge is validating the customer
value proposition offered by the connected ecosystem.
Security and Privacy
The heterogeneous and dynamic nature of the connectivity required between
devices, systems and end-users gives rise to several security challenges, whether
at the device, communication protocol or application level. In the connected
car scenario, in-vehicle applications need to secure the information exchange
between ECUs/onboard/telematics devices and user devices. Around-the-vehicle
applications need to handle vehicle-to-vehicle (V2V) security, and outside-the-
vehicle applications need to handle vehicle infrastructure (V2I) security.
Defining the Revenue Model
New Product/Service Offerings
Example: A newly launched car with demographically-
specific connected features.
• Identify a business-critical
product line/plan for a new
product.
• Develop a strategy around
the data value chain and
connected ecosystem.
PLAN
• Define commercializa-
tion roadmap.
• Develop a prototype/
MVP and confirm
the enhanced value/
benefits.
PILOT
• Develop pricing & engage-
ment model (oucome-based,
usage-based, gainsharing
model etc.).
PRESCRIBE
• Proliferate the offerings.
PROLIFERATE
1
2
3
4
• On-board an anchor
customer.
• Identify a business-critical
active device/product line.
• Device and data integration.
PLAN
• Gather ecosystem data.
• Develop hypothesis.
• Conduct a pilot and confirm
the enhanced value/benefits.
PILOT
• Define commercialization
roadmap.
• Develop pricing & engage-
ment model (outcome-based,
usage-based, gainsharing
model etc.).
PRESCRIBE
• Proliferate the offerings.
PROLIFERATE
Enhancing Product/Service Offerings
Example: Monitoring an installed packaging machine
and moving to a performance-based business model.
1
2
3
4
Figure 6
14. 14 KEEP CHALLENGING August 2015
Securing the communication at the protocol level requires that bandwidth, power
supply, processing capabilities and security features are balanced. Security and
privacy need to be addressed for all the data that is captured, stored, processed and
accessed across the technology chain and by different stakeholders. For example,
trust needs to be established for connected infrastructure components (e.g.,
resolution, authorization or certification authority) and actors within the network
(service invokers and providers), as does the accountability for actions performed
through the connected network and privacy for data handled by the infrastructure.
Governance, risk and compliance policies help businesses use appropriate
frameworks to identify risk, assess vulnerabilities, design and implement controls,
manage incidents and design forensic measures across the technology chain.
Additionally, the management of residual risk, testing and updates form essential
processes that need to be followed for designing resilient and connected solutions.
Technology Selection
Technological advances ensure that information is made available within the
connected network on an anywhere/anytime basis to authorized users so that
proactive decisions and actions can be made. However, businesses are struggling
to keep pace with rapid technology change and thus want to build enterprise-wide
architectures that can handle scale, interoperability, security and obsolescence
seamlessly.
The connected network DVC primarily comprises hardware devices (sensors, con-
trollers and gateways), communication protocols, device and data management
platforms and analytical tools. Given the plethora of choices and lack of standards,
selecting and “standardizing” these elements is a significant challenge. For
example, hardware selection is based on performance and interface analysis,
depending on factors such as I/O volume, latency, local processing and storage
requirements. Communication protocols are primarily selected on the basis of
bandwidth, latency, data footprint and security requirements. The selection of
device and data management platforms depends on scalability, flexibility, ease of
device management and client-side application
support, whereas the choice of analytical tools
is driven mainly by domain considerations and
the mathematical skills required to consume
the data.
Choosing the right technology depends on
a combination of the maturity level of the
connected infrastructure, perceived customer
value and business model selected.
Going Forward
Fast-changing technology is disrupting the
industrial and consumer spaces. Customers are
now more aware and critical of the products
they use, and businesses are increasingly
aware of the opportunities posed by connected ecosystems to boost efficiencies
and establish a closer, more engaged relationship with customers and their needs.
Adopting a connected ecosystem requires significant collaboration across the orga-
nization, and because of the enterprise-wide impact, these initiatives should be
driven by executive leadership. A central, cross-functional entity should own the
connected agenda.
Choosing the right
technology depends on a
combination of the maturity
level of the connected
infrastructure, perceived
customer value and business
model selected.
15. CONNECTED PRODUCTS FOR THE INDUSTRIAL WORLD 15
Organizations must also understand the business requirements — their own KPIs
and that of their customers — the technology maturity of all ecosystem players, and
the market dynamics that define and inform the connected roadmap. In addition,
we suggest the following:
• Customer awareness: Businesses must generate insights around customer
processes and how their products and services are being used. For industrial
businesses, it is imperative to co-innovate with customers to realize the potential
of connected ecosystems.
• Dimension identification: Businesses must identify value along the four
dimensions described in this whitepaper, and extract results from at least one.
• Monetization: Filters must be applied to prioritize strategic initiatives that
advance the business agenda in terms of revenues and profitability.
• Business ecosystem creation: A winning partner ecosystem depends
on ownership of the DVC and fulfillment of required technology elements.
Onboarding the right customers and partners will be critical to success.
• Minimum viable product (MVP), models and culture: Businesses will need to
invest in new technologies and platforms and re-engineer current processes and
products as required by all partners in the initiative. Given the inevitable business
and operating model changes needed, a mindset shift is a must. Workforces will
be challenged to embrace new technology platforms and a digital approach to
engaging with customers and internal stakeholders.
Note: Code Halo™ is a trademark of Cognizant Technology Solutions.
16. 16 KEEP CHALLENGING August 2015
Footnotes
1
For more on smart products, see our white paper “The Rise of the Smart Product
Economy,” http://www.cognizant.com/InsightsWhitepapers/the-rise-of-the-smart-
product-economy-codex1249.pdf.
2
For more on Code Halos and innovation, read “Code Rules: A Playbook for Managing
at the Crossroads,” Cognizant Technology Solutions, June 2013, http://www.
cognizant.com/Futureofwork/Documents/code-rules.pdf, and the book, “Code Halos:
How the Digital Lives of People, Things, and Organizations are Changing the Rules of
Business,” by Malcolm Frank, Paul Roehrig and Ben Pring, published by John Wiley &
Sons. April 2014, http://www.wiley.com/WileyCDA/WileyTitle/productCd-1118862074.
html.
3
Sensorization refers to the process of adding/enabling multiple sensors within a
system/device to capture the data of interest around the device and its surroundings.
4
FFB (Foundation Fieldbus) is is an all-digital, serial, two-way communications system
that serves as the base-level network in a plant or factory automation environment.
5
HART (Highly Addressable Remote Transducer Protocol) is an early implementation
of Fieldbus.
6
Servitization refers to the inclusion and delivery of a service component to the
existing product portfolio to enhance the overall value of offerings for customers.
7
For more on this topic, see our white paper “Building a Code Halo Economy for
Insurance,” http://www.cognizant.com/InsightsWhitepapers/building-a-code-halo-
economy-for-insurance-codex1072.pdf.
8
Ibid.
About the Authors
Vivek Diwanji is a Chief Architect with Cognizant’s Engineering and Manufacturing
Solutions business unit. He has 18-plus years of experience in applied research and
innovative solutions and has worked in various domains, such as medical devices,
automotive, process control and defense. Vivek is author of several technical pub-
lications, and his research interests include intelligent systems, AI applications,
advanced controls and optimization. He has a master’s in electrical engineering
from Tennessee Tech. Vivek can be reached at Vivek.Diwanji@cognizant.com.
Nishant Verma is a Senior Business Consultant with Cognizant’s Engineering and
Manufacturing Solutions business unit. He has nine years of experience in consulting,
engineering (EPC) and project management in the engineering and manufacturing
domain. Nishant has worked in the FMCG, heavy machinery, automotive, tire, textile,
F&B and pharmaceuticals industries, and has interest in the areas of operations
and technology. Nishant holds an M.B.A. from S.P. Jain Institute of Management &
Research, Mumbai. He can be reached at Nishant.Verma@cognizant.com.