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The non-invasive and cuffless blood pressure (BP) and heart rate (HR) monitoring device is designed to help people to monitor their BP and HR regularly. A Photoplethysmogram (PPG) sensor was used to obtain the PPG signal needed for the BP and HR calculations. The performance of the BP and HR monitoring device was tested based on the accuracy of the readings obtained by comparing readings from the proposed device with the readings obtained by clinical instruments. The factors that are affecting the accuracy of the sensor are also discussed in this paper.

Since cloud computing is an essential component of any modern company (usually accounting for a considerable share of information technology (IT) infrastructure investment), consumers rely on cloud services. Data privacy and security are worries when data remains in third-party storage. Existing document version control systems are centralized and at risk from data loss, as seen by higher time utilization and incorrect document update procedures that allow modifications to a document without the awareness of other network operators. Underutilized peer resources might be leveraged to construct storage. According to this argument, an elevated level of data security may be obtained by encrypting the data and dispersing it among numerous nodes. In this study, we attempted to review the security of cloud systems when using the blockchain Ethereum, and cloud computing was briefly discussed with its advantages and disadvantages. The idea of a decentralized cloud was briefly demonstrated with blockchain technology. Furthermore, previous papers were reviewed and presented in tabular form. This dictated that there are still research gaps in the field of blockchain-based cloud computing systems. This study proposed a model for secured data storage over a decentralized cloud by blockchain Ethereum.

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Audio surveillance can provide an effective alternative to video surveillance in situations where the latter is impractical. Nevertheless, it is essential to note that audio recording raises privacy and legal concerns that require unambiguous consent from all parties involved. By utilizing keyword recognition, audio recordings can be filtered, allowing for the creation of a surveillance system that is activated by distress keywords. This paper investigates the performance of the Ensemble Bagged Trees (EBT) classifier in recognizing the distress keyword "Please" captured by a ceiling-mounted omnidirectional microphone in a room measuring 4.064m (length) x 2.54m (width) x 2.794m (height). The study analyzes the impact of different distances (0m, 1m, and 2m) and two directions (facing towards and away from the microphone) on recognition performance. Results indicate that the system is more sensitive and better able to identify targeted signals when they are farther away and facing toward the microphone. The validation process demonstrates excellent accuracy, precision, and recall values exceeding 98%. In testing, the EBT achieved a satisfactory recall rate of 86.7%, indicating moderate sensitivity, and a precision of 97.7%, implying less susceptibility to false alarms, a crucial feature of any reliable surveillance system. Overall, the findings suggest that a single omnidirectional microphone equipped with an EBT classifier is capable of detecting distress keywords in a low-noise enclosed room measuring up to 4.0 meters in length, 4.0 meters in width, and 2.794 meters in height. This study highlights the potential of employing an omnidirectional microphone and EBT classifier as an edge audio surveillance system for indoor environments.