Investigating the effects of key drivers on the energy consumption of nonresidential buildings: A data-driven approach integrating regularization and quantile regression

Energy ◽  
2021 ◽  
pp. 122720
Author(s):  
Xue Liu ◽  
Yong Ding ◽  
Hao Tang ◽  
Lingxiao Fan ◽  
Jie Lv
Keyword(s):  
Energy Consumption ◽  
Quantile Regression ◽  
Data Driven ◽  
Data Driven Approach ◽  
Key Drivers ◽  
Nonresidential Buildings

scholarly journals A data-driven approach to increasing the lifetime of IoT sensor nodes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shikhar Suryavansh ◽  
Abu Benna ◽  
Chris Guest ◽  
Somali Chaterji
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Data Transmission ◽  
Data Transfer ◽  
Streaming Data ◽  
Sensor Nodes ◽  
Data Driven ◽  
Wireless Sensor ◽  
Battery Lifetime ◽  
Data Driven Approach

AbstractData transmission accounts for significant energy consumption in wireless sensor networks where streaming data is generated by the sensors. This impedes their use in many settings, including livestock monitoring over large pastures (which forms our target application). We present Ambrosia, a lightweight protocol that utilizes a window-based timeseries forecasting mechanism for data reduction. Ambrosia employs a configurable error threshold to ensure that the accuracy of end applications is unaffected by the data transfer reduction. Experimental evaluations using LoRa and BLE on a real livestock monitoring deployment demonstrate 60% reduction in data transmission and a 2 $$\times$$ × increase in battery lifetime.

Extended-Range Prediction with Low-Dimensional, Stochastic-Dynamic Models: A Data-driven Approach

2012 ◽  
Author(s):  
Michael Ghil ◽  
Mickael D. Chekroun ◽  
Dmitri Kondrashov ◽  
Michael K. Tippett ◽  
Andrew Robertson ◽  
...  
Keyword(s):  
Dynamic Models ◽  
Data Driven ◽  
Stochastic Dynamic ◽  
Extended Range ◽  
Data Driven Approach ◽  
Low Dimensional
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