. in an environment enabled with sophisticated IoT solutions (e.g. a sensor-equipped automated warehouse) where a vector

[answerhappygod]

. in an environment enabled with sophisticated IoT solutions(e.g. a sensor-equipped automated warehouse) where a vector ofhundreds of measurements is collected periodically (e.g. once perhour), how would you design an unsupervised deep learning solutionfor anomaly detection based on e.g. years of monitoring?
Note1: IoT=Internet-of-things
Note2: anomaly detection means here detecting that something inthe controlled environment is not going right, is not as usual, isnot as it should be
Note3: for the sake of simplicity, we skip time dependencybetween measurements (which could be plausible instead) and we onlyrequire the definition and discussion of an algorithm (i.e.conceptual steps, choices, motivation) implementing an analyticspipeline to pursue the given goal (e.g. draw inspiration from theexamples provided in the lectures and labs).