A constant threat of exposure to toxic industrial gases poses a critical concern for the safety of industrial workers. The existing commercially available gas sensing and monitoring platforms are limited in their abil...
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ISBN:
(纸本)9798350338416
A constant threat of exposure to toxic industrial gases poses a critical concern for the safety of industrial workers. The existing commercially available gas sensing and monitoring platforms are limited in their abilities to monitor the potential leakages over a wide area and range of toxic gases. The latest advancements in technology have given birth to wearable sensing platforms that can be employed to monitor various physiological and environmental parameters. The use of these wearable devices has been constantly explored for monitoring and detection of toxic gases in the surrounding environment of a user. Unlike, traditional platforms wearable devices provide flexible, portable, and efficient solutions to the problems faced by workers in industries like mining and oil and gas. Current state-of-the-art wearable toxic gas monitoring solutions target a specific type of toxic gas and provide either an expensive or an uncomfortable device for the industrial worker. Also, these devices fail to provide useful information regarding the current health of the user. In this study, a multipurpose toxic gas sensing device has been presented along with the features of physiological signal measurement of the industrial worker. To broaden the scope of the device multiple metal oxide-based gas sensors were integrated and a custom-designed graphical user interface was designed to provide control and safety notifications to the user. Finally, a wireless connection to a custom-designed mobile application lets users analyze and report the data collected from the developed platform. Following the set of features introduced in the device, it can be used in any industrial setting as personal protective equipment to ensure the safety of the workers.
With the continuous promotion of 5G technology application in the electric power industry, how to realize the viewable, manageable and controllable power 5G virtual private network becomes an urgent problem to be solv...
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Photovoltaic (PV) modules are crucial components of contemporary distribution networks, but they have historically been employed primarily to provide profitable, clean, and green energy. An Adaptive Neuro Fuzzy Infere...
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This paper presents the active realization of a voltage mode fractional-order biquad filter which is capable of generating inverting low-pass, non-inverting band-pass along with a high-pass response. This filter has b...
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Due to limited power supply and long-life service requirements for wireless sensor nodes, energy and time-efficient methods are critical to in the wireless body area networks (WBAN). Link adaptation (LA) technique, in...
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ISBN:
(纸本)9781665471039
Due to limited power supply and long-life service requirements for wireless sensor nodes, energy and time-efficient methods are critical to in the wireless body area networks (WBAN). Link adaptation (LA) technique, in which modulation and coding are applied to change per channel conditions to maximize link throughput are widely investigated in the field of mobile communications. On the basis of LA and transmit power control (TPC) techniques, we propose a model-based calibration scheme to maintain a transmit power threshold table WBAN which satisfies the target quality of service (QoS) while minimizing transmission power of sensor nodes. Rather than existing methods that compare the SNR threshold with instantaneous channel SNR, we contrast the target bit error rate (BER) with instantaneous received BER, and calibrate the path loss and shadowing model, and receiver sensitivity. The proposed method lower bounds the transmit power given a pair of prescribed data rate and BER for a set of feasible combinations of modulation and coding schemes (MCSs). The performance evaluation show that the proposed method outperforms previous link adaptation methods in execution overheads and energy efficiency.
With their ability to analyse and learn from complex data, neural networks have emerged as an ubiquitous machine learning tool with applications in many industries. Despite the success of neural networks in various ta...
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The Hybrid Distribution Transformer (HDT) combines the main winding of a power frequency transformer used for voltage conversion with a power electronic converter. HDT can utilize the controllable capacity of the conv...
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applications of multilevel inverters (MLIs) are increasing extensively. Despite many advantages of MLIs, poor reliability of MLIs is a major concern as MLIs consist of a large number of semiconductor switches. Fault-t...
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Intelligent transportation systems rely heavily on automatic vehicle license plate recognition (AVLPR). This system is required for traffic control, electronic toll collection, and access to parking lots. Due to the c...
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The Internet of Things (IoT) is well-known as a new detecting paradigm for interacting with the real world in Industry 4.0. With IoT, major security concern arises in data communication between remote location and the...
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