Identity management has been ripe for disruption over the past few years due to recurring incidents of data breaches that have led to personal information leaks and identity theft.The rise of blockchain technology has...Identity management has been ripe for disruption over the past few years due to recurring incidents of data breaches that have led to personal information leaks and identity theft.The rise of blockchain technology has paved the way for the development of self-sovereign identity(SSI)—a new class of user-controlled resilient identity management systems that are enabled by distributed ledger technology.This paper examines how SSI management can be used in a public transportation sector that spans different operators in multiple countries.Specifically,the paper explores how a blockchain-based decentralized identity management system can draw on the SSI framework to provide high-level security and transparency for all involved parties in public transportation ecosystems.Accordingly,building on analyses of the existing public transportation ticketing solutions,we elicited requirements of a comparable system based on the SSI principles.Next,we developed a low-fidelity prototype to showcase how passengers can utilize standardized travel credentials that are valid across different transportation networks in Europe.The proposed system eliminates the need for multiple travel cards(i.e.,one for each transportation provider)and empowers individuals to have better control over the use of their identities while they utilize interoperable ticketing systems across Europe.Overall,building on the public transportation case,we offer a proof-of-concept that shows how individuals can better manage their identity credentials via the SSI framework.展开更多
The aim of maintenance is to reduce the number of failures in equipment and to avoid breakdowns that may lead to disruptions during operations.The objective of this study is to initiate the development of a predictive...The aim of maintenance is to reduce the number of failures in equipment and to avoid breakdowns that may lead to disruptions during operations.The objective of this study is to initiate the development of a predictive maintenance solution in the shipping industry based on a computational artificial intelligence model using real-time monitoring data.The data analysed originates from the historical values from sensors measuring the vessel´s engines and compressors health and the software used to analyse these data was R.The results demonstrated key parameters held a stronger influence in the overall state of the components and proved in most cases strong correlations amongst sensor data from the same equipment.The results also showed a great potential to serve as inputs for developing a predictive model,yet further elements including failure modes identification,detection of potential failures and asset criticality are some of the issues required to define prior designing the algorithms and a solution based on artificial intelligence.A systematic approach using big data and machine learning as techniques to create predictive maintenance strategies is already creating disruption within the shipping industry,and maritime organizations need to consider how to implement these new technologies into their business operations and to improve the speed and accuracy in their maintenance decision making.展开更多
文摘Identity management has been ripe for disruption over the past few years due to recurring incidents of data breaches that have led to personal information leaks and identity theft.The rise of blockchain technology has paved the way for the development of self-sovereign identity(SSI)—a new class of user-controlled resilient identity management systems that are enabled by distributed ledger technology.This paper examines how SSI management can be used in a public transportation sector that spans different operators in multiple countries.Specifically,the paper explores how a blockchain-based decentralized identity management system can draw on the SSI framework to provide high-level security and transparency for all involved parties in public transportation ecosystems.Accordingly,building on analyses of the existing public transportation ticketing solutions,we elicited requirements of a comparable system based on the SSI principles.Next,we developed a low-fidelity prototype to showcase how passengers can utilize standardized travel credentials that are valid across different transportation networks in Europe.The proposed system eliminates the need for multiple travel cards(i.e.,one for each transportation provider)and empowers individuals to have better control over the use of their identities while they utilize interoperable ticketing systems across Europe.Overall,building on the public transportation case,we offer a proof-of-concept that shows how individuals can better manage their identity credentials via the SSI framework.
文摘The aim of maintenance is to reduce the number of failures in equipment and to avoid breakdowns that may lead to disruptions during operations.The objective of this study is to initiate the development of a predictive maintenance solution in the shipping industry based on a computational artificial intelligence model using real-time monitoring data.The data analysed originates from the historical values from sensors measuring the vessel´s engines and compressors health and the software used to analyse these data was R.The results demonstrated key parameters held a stronger influence in the overall state of the components and proved in most cases strong correlations amongst sensor data from the same equipment.The results also showed a great potential to serve as inputs for developing a predictive model,yet further elements including failure modes identification,detection of potential failures and asset criticality are some of the issues required to define prior designing the algorithms and a solution based on artificial intelligence.A systematic approach using big data and machine learning as techniques to create predictive maintenance strategies is already creating disruption within the shipping industry,and maritime organizations need to consider how to implement these new technologies into their business operations and to improve the speed and accuracy in their maintenance decision making.
