I am starting to work on an article digging into which existing disciplines or domains we should look to for algorithms and analytical methods in order to gain the most insight from the growing Internet-of-Things (IoT).<p>Some that I have thought of:<p>1] Signal Processing - filtering<p>2] Array Processing - wave detection and location&#x2F;shape<p>3] Industrial control systems - local logic and system-wide control<p>4] Stock and commodity analysis - time series and trend detection<p>5] Medical instruments like EEG  - spike detection<p>6] Quality Assurance&#x2F;Control - thresholds and ceilings<p>7] Systems monitoring (server and network monitoring)<p>8] Motif detection and matching - more complex time series pattern detection<p>9] Agent-based modeling<p>What domains am I missing? What algorithm or statistical approaches might have languished in academia for years but might become important as sensors become cheap and pervasive along with cheap computation both at the edge and in the cloud?<p>If I pull a quote from this thread in the post I will attribute it to your HN username.  The post will eventually appear at computationalimagination.com<p>Thanks
Ask HN: What disciplines will contribute most to IoT analytical methods?