A Novel Framework of an IOT-Blockchain-Based Intelligent System

With the growing need of technology into varied fields, dependency is getting directly proportional to ease of user-friendly smart systems. The advent of artificial intelligence in these smart systems has made our lives easier. Several Internet of Things- (IoT-) based smart refrigerator systems are emerging which support self-monitoring of contents, but the systems lack to achieve the optimized run time and data security. Therefore, in this research, a novel design is implemented with the hardware level of integration of equipment with a more sophisticated software design. It was attempted to design a new smart refrigerator system, which has the capability of automatic self-checking and self-purchasing, by integrating smart mobile device applications and IoT technology with minimal human intervention carried through Blynk application on a mobile phone. The proposed system automatically makes periodic checks and then waits for the owner’s decision to either allow the system to repurchase these products via Ethernet or reject the purchase option. The paper also discussed the machine level integration with artificial intelligence by considering several features and implemented state-of-the-art machine learning classifiers to give automatic decisions. The blockchain technology is cohesively combined to store and propagate data for the sake of data security and privacy concerns. In combination with IoT devices, machine learning, and blockchain technology, the proposed model of the paper can provide a more comprehensive and valuable feedback-driven system. The experiments have been performed and evaluated using several information retrieval metrics using visualization tools. Therefore, our proposed intelligent system will save effort, time, and money which helps us to have an easier, faster, and healthier lifestyle.

Are smart contracts too smart for Supply Chain 4.0? A blockchain framework to mitigate challenges

PurposeSmart contracts are self-executing computer programmes that have the potential to be used in several applications instead of traditional written contracts. With the recent rise of smart systems (e.g. Internet of things) and digital platforms (e.g. blockchain), smart contracts are gaining high interest in both business and academia. In this work, a framework for smart contracts was proposed with using reputation as the system currency, and conducts currency mining through fulfilling the physical commitments that are agreed upon.Design/methodology/approachA game theory model is developed to represent the proposed system, and then a system dynamics simulator is used to check the response of the blockchain with different sizes.FindingsThe numerical results showed that the proposed system could identify the takeover attacks and protect the blockchain from being controlled by an outsider. Another important finding is that careful setting of the maximum currency amount can improve the scalability of the blockchain and prevent the currency inflation.Research limitations/implicationsThis work is proposed as a conceptual framework for supply chain 4.0. Future work will be dedicated to implement and experiment the proposed framework for other characteristics that may be encountered in the context of supply chain 4.0, such as different suppliers' tiers, different customer typologies and smart logistics applications, which may reveal other challenges and provide additional interesting insights.Practical implicationsBy using the proposed framework, smart contracts and blockchains can be implemented to handle many issues in the context of operations and supply chain 4.0, especially in times of turbulence such as the COVID-19 global pandemic crisis.Originality/valueThis work emphasizes that smart contracts are not too smart to be applied in the context of supply chain 4.0. The proposed framework of smart contracts is expected to serve supply chain 4.0 by automating the knowledge work and enabling scenario planning through the game theory model. It will also improve online transparency and order processing in real-time through secured multitier connectivity. This can be applied in global supply chain functions backed with digitization, notably during the time of the pandemic, in which e-commerce and online shopping have changed the rules of the game.

Secure Authentication Scheme Using Diffie–Hellman Key Agreement for Smart IoT Irrigation Systems

Smart irrigation is considered one of the most significant agriculture management systems worldwide, considering the current context of water scarcity. There is a clear consensus that such smart systems will play an essential role in achieving the economic growth of other vital sectors. In general, the consequences of global warming and the unavailability of clean water sources for the agricultural sector are clear indications that the demand for these systems will increase in the near future, especially considering the recent expansions in the use of the Internet of Things (IoT) and Wireless Sensor Network (WSN) technologies, which have been employed in the development of such systems. An obvious result is that security challenges will be one of the main obstacles to attaining the widespread adoption of such systems. Therefore, this paper proposes a secure authentication scheme using Diffie–Hellman key agreement for smart IoT irrigation systems using WSNs. This scheme is based on Diffie–Hellman and one-way hash cryptographic functions in order to support the basic security services with a high data rate and ability to resist well-known attacks. The Burrows–Abadi–Needham (BAN) logic model is used to verify the proposed scheme formally. Based on various possible attack scenarios, a resistance analysis of the proposed scheme is discussed. Further analyses are performed in terms of the storage size, intercommunication, and running time costs. Therefore, the proposed scheme not only can be considered a secure authentication scheme but is also practical for smart IoT irrigation systems due to its reasonable efficiency factors.

Polyelectrolyte Complexes of Ciprofloxacin and Lidocaine Improve Wound Healing in Deep Second Degree Burns and Reduce in Vitro Ciprofloxacin Cytotoxicity in Fibroblasts

The development of new treatments capable of controlling infections and pain related to burns continues to be a challenge. Antimicrobials are necessary tools, but these can be cytotoxic for regenerating cells.In this study, antibiotic-anesthetic smart systems obtained by ionic complexation of polyelectrolytes with ciprofloxacin and lidocaine were obtained as film and hydrogel. The complexation of ciprofloxacin with natural polyelectrolytes efficiently contributed to increasing biocompatibility in a primary culture of isolated fibroblasts. In addition, the relative levels of the proteins integrin β1 and p-FAK involved in cell migration were increased with no modifications in cell mobility. Their evaluation in a deep second-degree burn model revealed fast reepithelization, with appendage conservation and complete dermis organization. Encouragingly, we found that both the film and the hydrogel showed a significantly superior performance compared to the reference treatment of silver sulfadiazine cream. This work highlights the great potential of this smart system as an attractive dressing for burns, which surpasses currently available treatments.

A decade of research on patterns and architectures for IoT security

Security of the Internet of Things (IoT)-based Smart Systems involving sensors, actuators and distributed control loop is of paramount importance but very difficult to address. Security patterns consist of domain-independent time-proven security knowledge and expertise. How are they useful for developing secure IoT-based smart systems? Are there architectures that support IoT security? We aim to systematically review the research work published on patterns and architectures for IoT security (and privacy). Then, we want to provide an analysis on that research landscape to answer our research questions. We follow the well-known guidelines for conducting systematic literature reviews. From thousands of candidate papers initially found in our search process, we have systematically distinguished and analyzed thirty-six (36) papers that have been peer-reviewed and published around patterns and architectures for IoT security and privacy in the last decade (January 2010–December 2020). Our analysis shows that there is a rise in the number of publications tending to patterns and architectures for IoT security in the last three years. We have not seen any approach of applying systematically architectures and patterns together that can address security (and privacy) concerns not only at the architectural level, but also at the network or IoT devices level. We also explored how the research contributions in the primary studies handle the different issues from the OWASP Internet of Things (IoT) top ten vulnerabilities list. Finally, we discuss the current gaps in this research area and how to fill in the gaps for promoting the utilization of patterns for IoT security and privacy by design.

Enhancing Smart System Platforms; Factors Affecting People's Intentions toward Smart Homes in Jordan

Smart systems are going to transform the social life of modern society. Notwithstanding the benefits of these systems, its use is still low in developing world including Jordan. This study aims to construct a novel model to identify the factors that affect people’s intention to use smart systems in their homes. A survey was conducted on 650 individuals among which 550 valid questionnaires were considered in Jordan. The collected data were analyzed for descriptive analysis and further to valid the hypothesis using Structural Equation Modeling. The findings showed that there is a significant relationship between individuals’ attitudes related to PU and PEOU with their intention toward using smart systems in their lifestyle. It indicated that the research model explains 68.6% of the variance in the individual’s intention to use smart systems in their residence. Practically, it fruitful to the top management of IT companies that offers smart systems. Moreover, enhancing the current systems and organizing a strategic plan for implementation within best practice.

Big Data in Railway O&M

Railway systems are complex with respect to technology and operations with the involvement of a wide range of human actors, organizations and technical solutions. For the operations and control of such complexity, a viable solution is to apply intelligent computerized systems, for instance, computerized traffic control systems for coordinating airline transportation, or advanced monitoring and diagnostic systems in vehicles. Moreover, transportation assets cannot compromise the safety of the passengers by only applying operation and maintenance activities. Indeed, safety is a more difficult goal to achieve using traditional maintenance strategies and computerized solutions come into the picture as the only option to deal with complex systems interacting among them and trying to balance the growth in technical complexity together with stable and acceptable dependability indexes. Big data analytics are expected to improve the overall performance of the railways supported by smart systems and Internet-based solutions. Operation and Maintenance will be application areas, where benefits will be visible as a consequence of big data policies due to diagnosis and prognosis capabilities provided to the whole network of processes. This chapter shows the possibilities of applying the big data concept in the railway transportation industry and the positive effects on technology and operations from a systems perspective.