  Clinical research of wound assessment focused on physical appearance of wound
i.e. wound width, shape, color etc. Although, wound appearance is most crucial
factors to influence healing process. however, apart from wound appearance
other factors also contribute in healing process. Wound internal and external
environment is one such factor that may show positive or negative impact on
healing. Internet of things extensively popular during last decade, due to its
heavy applications in almost all domains i.e. agriculture, health, marketing,
banking, home etc. Therefore, in current research we proposed IoT based
intelligent wound assessment system, for assessment of wound status and apply
entropy and information gain statistics of decision tree to reflect status of
wound assessment by categorization of assessment results in one of three class
i.e. good, satisfactory or alarming. We implemented decision tree in MATLAB, in
which we select ID3 algorithm for decision tree which based on entropy and
information gain for the selection of best feature to split the tree. The
efficient feature split of decision tree improved training accuracy rate and
performance of decision tree.
