Development and evaluation of a low-cost data acquisition system using heterogeneous sensors

Zubair, Muhammad; Ishaq, Hafiza Nida; Raza, Ali; Maqbool, Hafiz Farhan; Zafar, Saqib

doi:10.1504/ijsnet.2022.125274

Cited by 3 publications

(1 citation statement)

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“…Scientific assessment of the carbon footprint of tourism activities and the carbon absorption of natural ecosystems, i.e. the carbon balance of tourism ecosystems, is important for the quantitative analysis of the carbon balance of tourism activities and the formulation of low carbon management decisions in nature reserves [17][18].…”

Section: Carbon Revenue and Expenditure Evaluation Modelmentioning

confidence: 99%

Assessment System of Natural Environment Protection Based on Energy Efficiency

2023

NEP

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Since the reform and opening up, China's economy has developed at a rapid pace, and the impact of industrial development and social change on the natural environment has become more diverse and profound. In evaluating the economic value of nature reserves, we often have to consider their current economic value, and past values appear to be meaningless, which makes it necessary to ensure both a reliable basis for the calculation criteria when calculating the value of reserves, and the use of time-recent This makes it necessary to ensure that the criteria for calculating the value of protected areas are reliable and that the most recent data are used. Therefore, this paper uses Nature Reserve C as an example to construct an assessment system for natural environment protection based on energy efficiency. The paper begins with a brief introduction of the evaluation principles and the carbon balance evaluation model, followed by the design of the nature reserve evaluation system and the general architecture of the system, and finally the analysis of the natural resource value and the economic value of the nature reserve.

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Section: Carbon Revenue and Expenditure Evaluation Modelmentioning

confidence: 99%

Assessment System of Natural Environment Protection Based on Energy Efficiency

2023

NEP

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Gait asymmetrical evaluation of lower limb amputees using wearable inertial sensors

Maqbool,

Mahmood,

Ali

et al. 2024

Heliyon

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Multi-Class Classification of Human Activity and Gait Events Using Heterogeneous Sensors

Javed,

Raza,

Maqbool

et al. 2024

JSAN

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The control of active prostheses and orthoses requires the precise classification of instantaneous human activity and the detection of specific events within each activity. Furthermore, such classification helps physiotherapists, orthopedists, and neurologists in kinetic/kinematic analyses of patients’ gaits. To address this need, we propose an innovative deep neural network (DNN)-based approach with a two-step hyperparameter optimization scheme for classifying human activity and gait events, specific for different motor activities, by using the ENABL3S dataset. The proposed architecture sets the baseline accuracy to 93% with a single hidden layer and offers further improvement by adding more layers; however, the corresponding number of input neurons remains a crucial hyperparameter. Our two-step hyperparameter-tuning strategy is employed which first searches for an appropriate number of hidden layers and then carefully modulates the number of neurons within these layers using 10-fold cross-validation. This multi-class classifier significantly outperforms prior machine learning algorithms for both activity and gait event recognition. Notably, our proposed scheme achieves impressive accuracy rates of 98.1% and 99.96% for human activity and gait events per activity, respectively, potentially leading to significant advancements in prosthetic/orthotic controls, patient care, and rehabilitation programs’ definition.

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Development and evaluation of a low-cost data acquisition system using heterogeneous sensors

Cited by 3 publications

References 0 publications

Assessment System of Natural Environment Protection Based on Energy Efficiency

Assessment System of Natural Environment Protection Based on Energy Efficiency

Gait asymmetrical evaluation of lower limb amputees using wearable inertial sensors

Multi-Class Classification of Human Activity and Gait Events Using Heterogeneous Sensors

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