Yiwei Huang, Tingting Ruan, Qiaoyun Yi, Tingting Wang, Zhihua Guo
The health literacy questionnaire among the aged in Changsha, China: confirmatory factor analysis
BMC public health
accurate air pollution prediction vital residents wellbeing research introduces secure air quality monitoring system using neural networks blockchain robust analysis precise predictions early pollution detection blockchain guarantees data integrity security transparency goals include realtime air quality data secure blockchain recording enhanced safety informed decisions research integrates blockchain iot short longterm air quality monitoring utilizing optimized neural network iot sensors collect pm25 pm10 co no2 so2 processed noise removal normalization feature extraction using ntuple contrastive learning predictions utilize graph attentionbased deep residual shrinkage network bidirectional long short term memory grnbtm categorized five levels adaptive bowerbird algorithm optimizes parameters reducing computational complexity blockchain integration ensures secure tamperproof data storage lightweight consensusbased algorithm grnbtm models air quality monitoring performance extensively simulated analyzed 30min 2h 1day 1month intervals demonstrating superior performance existing techniques