SVM Prediction Model Interface for Plant Contaminates

In today's time, our nature is fighting against many life-threatening problems which can even threaten the existence of life on Earth. Pollution one deadliest among them. It caused primarily by means air, water and land but air pollution most severe dreadful introduction toxic substances like oxides Sulphur, nitrogen carbon into atmosphere making it unfit for living beings. Along with humans, plants have also become a victim to it, this fact mostly ignored. A model has been designed predict effect plants. Image samples 5 Indian oxygen rich namely Ocimum Tenuiflorum, Sansevieria Trifasciata, Chlorophytum Comosum, Azadirachta Indica taken analysis various properties shape, color, corners texture were considered from these input RGB images. As consequence index value, certain calculations performed results are compared threshold values. Based range in calculated lie, will be categorized category depicts severity level environment. After applying images, dataset was prepared SVM classification trained an accuracy 85%. presented form interactive user interface Plants integral part should not