Falling is among the most damaging event elderly people may experience. With the ever-growing aging population, there is an urgent need for the development of fall detection systems. Thanks to the rapid development of sensor networks and the Internet of Things (IoT), human-computer interaction using sensor fusion has been regarded as an effective method to address the problem of fall detection. In this paper, we provide a literature survey of work conducted on elderly fall detection using sensor networks and IoT. Although there are various existing studies which focus on the fall detection with individual sensors, such as wearable ones and depth cameras, the performance of these systems are still not satisfying as they suffer mostly from high false alarms. Literature shows that fusing the signals of different sensors could result in higher accuracy and lower false alarms, while improving the robustness of such systems. We approach this survey from different perspectives, including data collection, data transmission, sensor fusion, data analysis, security, and privacy. We also review the benchmark data sets available that have been used to quantify the performance of the proposed methods. The survey is meant to provide researchers in the field of elderly fall detection using sensor networks with a summary of progress achieved up to date and to identify areas where further effort would be beneficial.
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Decentralized Finance (DeFi) takes the promise of blockchain a step further and aims to transform traditional financial products into trustless and transparent protocols that run without involving intermediaries. Similar to how 2017 was the year of ICOs, 2020 was the year of DeFi, with more than fifteen billion dollars of total investments. The decentralized platforms utilize oracles to retrieve asset data from the external world, but their choice and management criteria are often unknown to the end-users. If oracles are poorly selected or managed, the funds of a rising number of investors are inevitably in danger. The issue, known as “the oracle problem”, which makes real-world applications controversial and debated due to the loss of decentralization, had recently drawn attention to DeFi, given the crescent number of related hacks that caused the loss of millions of dollars held in DeFi projects. Through a multivocal approach that considers academic papers, whitepapers, preprints, and opinion posts, this study aims to shed light on the pattern that identifies the oracle problem in DeFi and outline the most promising ways to overcome the related weaknesses. This research supports the view that the oracle problem in decentralized finance bears specific characteristics which require standardization and appropriate economic incentives to be addressed.
Smart contracts have been argued to be a means of building trust between parties by providing a self-executing equivalent of legal contracts. And yet, code does not always perform what it was originally intended to do, which resulted in losses of millions of dollars. Static verification of smart contracts is thus a pressing need. This paper presents an approach to verifying smart contracts written in Solidity by automatically translating Solidity into Java and using KeY, a deductive Java verification tool. In particular, we solve the problem of rolling back the effects of aborted transactions by exploiting KeY's native support of JavaCard transactions. We apply our approach to a smart contract which automates a casino system, and discuss how the approach addresses a number of known shortcomings of smart contract development in Solidity.
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