Visions and Challenges in Managing and Preserving Data to Measure Quality of Life

Health-related data analysis plays an important role in self-knowledge, disease prevention, diagnosis, and quality of life assessment. With the advent of data-driven solutions, a myriad of apps and Internet of Things (IoT) devices (wearables, home-medical sensors, etc) facilitates data collection and provide cloud storage with a central administration. More recently, blockchain and other distributed ledgers became available as alternative storage options based on decentralised organisation systems. We bring attention to the human data bleeding problem and argue that neither centralised nor decentralised system organisations are a magic bullet for data-driven innovation if individual, community and societal values are ignored. The motivation for this position paper is to elaborate on strategies to protect privacy as well as to encourage data sharing and support open data without requiring a complex access protocol for researchers. Our main contribution is to outline the design of a self-regulated Open Health Archive (OHA) system with focus on quality of life (QoL) data.Comment: DSS 2018: Data-Driven Self-Regulating System

LEVERAGING BLOCKCHAIN TECHNOLOGY TO REVAMP THE VEHICLE ELECTRIFICATION JOURNEY: PERSPECTIVES OF ACCOUNTABILITY AND ECONOMIC CIRCULARITY

The automotive industry is undergoing a significant transition accelerated by global emission regulations for a phase out of internal combustion engines (ICEs) and a transition toward the adoption of electric vehicles (EVs). While regulatory measures and incentivized adoption for EVs presents opportunities for reducing emissions and promoting sustainability, it also poses complex challenges. The EV industry faces potential production challenges, particularly in the sourcing, manufacturing, and lifecycle management of critical minerals and raw materials for electric vehicle batteries (EVBs). With a heavy reliance on a steady and diversified supply of critical minerals such as lithium, cobalt and rare earth elements, the finite nature of mineral resources poses long-term challenges for EV stakeholders. The recent measures instituted by government regulations do recognize the need for EV stakeholder accountability, requiring substantiated evidentiary proof by way of data collection and analysis mandating resource recapture and reintroduction into circularity, environmental benefits, and real-time data availability. By implementing clear end-of-life requirements such as collection targets, material recovery goals, and extended producer responsibility, EV producers are held responsible for managing the entire lifecycle of electric vehicle batteries (EVBs). Government regulations are aimed at bolstering sustainability standards, and a high degree of accountability for all battery products, showing a clear shift towards circular economic standards. This culminating experience project explores the role of collaborative initiatives and innovative technological frameworks, particularly, blockchain, smart contracts, and Nash equilibrium game theory, in addressing sustainability challenges within the EV ecosystem. The research questions are: (RQ1) How does the strategic application of blockchain technology within a circular economic framework facilitate cooperation among stakeholders in the EV industry, leading to improved oversight, enhanced accountability, and guided decision-making? (RQ2) How can the implementation of private-permissioned blockchain technology, particularly through smart contracts, be strategically employed to enhance transparency, traceability, and sustainability throughout the lifecycle of electric vehicles, within the broader context of the EV ecosystem? (RQ3) Why should EV industry stakeholders engage in a consortium, that is driven by blockchain technology, smart contracts, Nash Equilibrium game theory, and what are the potential effects? The findings for each question are: (Q1) The partnership among RCS, IBM, Ford, exemplified how integrating blockchain into a circular economic framework can establish oversight, ensure accountability, and enable informed decision-making with traceable and transparent data circularity. Ford notably improved its cobalt due diligent management system, marked by a notable forty-six percentage point within one year, demonstrating its commitment to responsible sourcing and regulatory compliance. (Q2) Private-permissioned blockchain networks, especially with smart contracts, automate performance obligations, without an intermediary interaction, strengthening self-governance within a decentralized network. The consensus mechanism, integral to blockchain architecture, enhances accountability among EV stakeholders by validating and authenticating transactions. Opting for a consensus algorithm, emphasizing participant reputation over computational power, reduces reliance on resources while maintaining network integrity. (Q3) EV stakeholders and their tier-1 suppliers, in a consortium, are incentivized to uphold their reputation and branding through adherence to ethical and sustainable practices facilitated in a blockchain network. By doing so, they contribute to the overall stability of the industry and the circular economic framework, as mutual benefits are maximized, unilateral deviations are discouraged, and collaborative dynamics are fostered. The conclusions are: (Q1) EV producers involved in circular economic initiatives can be perceived as collaborative partners that prioritize collective success over individual gain, fostering positive brand associations with teamwork and partnership. (Q2) By aligning incentives, fostering collaboration, and leveraging data-driven insights, EV producers and their suppliers can optimize resource use, minimize waste, and contribute to the transition towards a more sustainable economic model. (Q3) By adhering to ethical and sustainable practices the equilibrium ensures that EV stakeholders maintain trust and credibility, promoting a sustainable ecosystem for the EV industry within the circular economy

Risks associated with Logistics 4.0 and their minimization using Blockchain

Currently we are saying that we are at the dawn of the fourth revolution, which is marked by using cyber-physical systems and the Internet of Things. This is marked as Industry 4.0 (I4.0). With Industry 4.0 is also closely linked concept Logistics 4.0. The highly dynamic and uncertain logistic markets and huge logistic networks require new methods, products and services. The concept of the Internet of Things and Services (IoT&S), Big Data/Data Mining (DM), cloud computing, 3D printing, Blockchain and cyber physical system (CPS) etc. seem to be the probable technical solution for that. However, associated risks hamper its implementation and lack a comprehensive overview. In response, the paper proposes a framework of risks in the context of Logistics 4.0. They are here economic risks, that are associated e.g. with high or false investments. From a social perspective, risks the job losses, are considered too. Additionally, risks can be associated with technical risks, e.g. technical integration, information technology (IT)-related risks such as data security, and legal and political risks, such as for instance unsolved legal clarity in terms of data possession. It is therefore necessary to know the potential risks in the implementation process.Web of Science101857

Blockchain For Food: Making Sense of Technology and the Impact on Biofortified Seeds

The global food system is under pressure and is in the early stages of a major transition towards more transparency, circularity, and personalisation. In the coming decades, there is an increasing need for more food production with fewer resources. Thus, increasing crop yields and nutritional value per crop is arguably an important factor in this global food transition. Biofortification can play an important role in feeding the world. Biofortified seeds create produce with increased nutritional values, mainly minerals and vitamins, while using the same or less resources as non-biofortified variants. However, a farmer cannot distinguish a biofortified seed from a regular seed. Due to the invisible nature of the enhanced seeds, counterfeit products are common, limiting wide-scale adoption of biofortified crops. Fraudulent seeds pose a major obstacle in the adoption of biofortified crops. A system that could guarantee the origin of the biofortified seeds is therefore required to ensure widespread adoption. This trust-ensuring immutable proof for the biofortified seeds, can be provided via blockchain technology

On Blockchain We Cooperate: An Evolutionary Game Perspective

Cooperation is fundamental for human prosperity. Blockchain, as a trust machine, is a cooperative institution in cyberspace that supports cooperation through distributed trust with consensus protocols. While studies in computer science focus on fault tolerance problems with consensus algorithms, economic research utilizes incentive designs to analyze agent behaviors. To achieve cooperation on blockchains, emerging interdisciplinary research introduces rationality and game-theoretical solution concepts to study the equilibrium outcomes of various consensus protocols. However, existing studies do not consider the possibility for agents to learn from historical observations. Therefore, we abstract a general consensus protocol as a dynamic game environment, apply a solution concept of bounded rationality to model agent behavior, and resolve the initial conditions for three different stable equilibria. In our game, agents imitatively learn the global history in an evolutionary process toward equilibria, for which we evaluate the outcomes from both computing and economic perspectives in terms of safety, liveness, validity, and social welfare. Our research contributes to the literature across disciplines, including distributed consensus in computer science, game theory in economics on blockchain consensus, evolutionary game theory at the intersection of biology and economics, bounded rationality at the interplay between psychology and economics, and cooperative AI with joint insights into computing and social science. Finally, we discuss that future protocol design can better achieve the most desired outcomes of our honest stable equilibria by increasing the reward-punishment ratio and lowering both the cost-punishment ratio and the pivotality rate

Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches

Peer-to-peer (P2P) energy trading has emerged as a next-generation energy management mechanism for the smart grid that enables each prosumer of the network to participate in energy trading with one another and the grid. This poses a significant challenge in terms of modeling the decision-making process of each participant with conflicting interest and motivating prosumers to participate in energy trading and to cooperate, if necessary, for achieving different energy management goals. Therefore, such decision-making process needs to be built on solid mathematical and signal processing tools that can ensure an efficient operation of the smart grid. This paper provides an overview of the use of game theoretic approaches for P2P energy trading as a feasible and effective means of energy management. As such, we discuss various games and auction theoretic approaches by following a systematic classification to provide information on the importance of game theory for smart energy research. Then, the paper focuses on the P2P energy trading describing its key features and giving an introduction to an existing P2P testbed. Further, the paper zooms into the detail of some specific game and auction theoretic models that have recently been used in P2P energy trading and discusses some important finding of these schemes.Comment: 38 pages, single column, double spac

Cyber diplomacy: defining the opportunities for cybersecurity and risks from artificial intelligence, IoT, blockchains, and quantum computing

Cyber diplomacy is critical in dealing with the digital era’s evolving cybersecurity dangers and possibilities. This article investigates the impact of Artificial Intelligence (AI), the Internet of Things (IoT), Blockchains, and Quantum Computing on cyber diplomacy. AI holds the potential for proactive threat identification and response, while IoT enables international information sharing. Blockchains enable secure data sharing and document verification, but they also pose new threats, such as AI-driven cyber-attacks, IoT privacy breaches, blockchain vulnerabilities, and the potential for quantum computing to break encryption. This article conducts case study reviews in combination with secondary data analysis and emphasises the value of international cooperation in developing global norms and frameworks to control responsible technology adoption. Cyber diplomacy can promote cybersecurity, protect national interests, and foster mutual trust among nations in the digital sphere by capitalising on possibilities and reducing threats

Assessing Blockchain’s Potential to Ensure Data Integrity and Security for AI and Machine Learning Applications

The increasing use of data-centric approaches in the fields of Machine Learning and Artificial Intelligence (ML/AI) has raised substantial issues over the security, integrity, and trustworthiness of data. In response to this challenge, Blockchain technology offered a promising and practical solution, as its inherent characteristics as a decentralized distributed ledger, coupled with cryptographic processes, offer an unprecedented level of data confidentiality and immutability. This study examines the mutually beneficial connection between Blockchain technology and ML/AI, using Blockchain\u27s inherent capacity to protect against unauthorized alterations of data during the training phase of ML models. The method involves building valid blocks of data from the training dataset and then sending them to the mining process using smart contracts and the Proof of Work (PoW) consensus method. Using SHA256 to produce a cryptographic signature for each data block improves the aforementioned procedure. The public Ethereum blockchain serves as a secure repository for these signatures, whereas a cloud-based infrastructure houses the original data file. Particularly during the training phase of Machine Learning (ML) models, this cryptographic framework is critical in ensuring the data verification procedure. This research investigates the potential collaboration between Blockchain technology and ML/AI, bolstering data quality and trust to enhance data-driven decision-making fortifying the models\u27 ability to provide precise and dependable results