I have been a long time lurker. Posting here for the first time.
I have sensor data (pressure and temperature measurements recorded as time series) at various locations. I have the latitudes and longitudes of these locations.
Often, pressure isn’t recorded owing to mainly cost related concerns. I have been tasked to predict the pressure given the entire temperature series for a particular location. The data does not seem to have any visible trends.
I have the following data to build a model: latitude, longitude, timestamps, pressure, temperature, sensor type.
What would be a good approach to build a model that predicts the pressure for given times at a particular latitude and longitude?
Here are things I tried with limited success:
RNN/LSTM - I have seen models built for forecasting the same time series. How do I use RNNs to build a spatially dependent model?
WaveNet - I picked up the idea of WaveNet from one of @jeremy’s posts on the forum. I can use WaveNet to generate time series, but, how do I pass a location to WaveNet?
Any suggestions would be sincerely appreciated.