Tensor decompositions are defined for deep learning networks and active filter designs for the class of problems of event detection and wake word detection filters, for wildlife and demographic vocalization and footstep census and for landslide detection. The problems are proven Z complete from previous work, in published literature. An estimate on the minimal number of samples required to predict demographic and wildlife census and reasonably predict landslides within given confidence intervals is presented using clustered, stratified sampling.The Shaktiman(™) is introduced as a USB form factor IP 68 system for integration into computing for IoT applications using SoC RF solutions similar to BOMU and TOMU using the Shakti Risc V processor developed at IIT Madras. The Thunderboard Sense 2 module is directly integrated to 3D printed mathematical art to create solar lanterns for hymnology and early bird warning systems, for data logging, bioluminosity, early bird warning systems for natural disasters like landslides and other weather disturbances, using integrated temperature, humidity and hall sensors.Cloud integration with Google Firebase is used for a FaaS framework to the use of tensor decomposition in defining the architecture of deep learning and procedural A.I for event detection from multi sensor fusion. A commercial product already available through Shapeways.com, designed by the author is to be enhanced to add event detection and wake word detection functions for PID systems and natural disaster monitoring and prediction infrastructure to add to the existing pioneering efforts by IIT Mandi.Keywords: Disaster Prediction, Landslide, Footstep detection, Air Pollution Monitoring, Solar Garden Lamps, Hymnology, Early Bird Warning Systems, Indigenous Whistle Languages