Around 9.76 million peoples in the rural and semi-urban area are depend on the sericulture for their livelihood. Monitoring the health and environment of silk worm is a crucial factor of sericulture industry. Which is done manually by farmers or care taker by monitoring them time to time and keeping track of their environmental conditions which are favourable temperature and humidity. By automating this process lot of time, work and labour cost of farmers can be saved and utilized for other work. For doing so Arduino will be used which will be connected to temperature sensor, and humidity sensor which will be used for taking input signal from the system and define the current environment conditions of the system. The current environmental conditions will be compared by threshold values which will be which will be predefined. If the value of temperature is greater than threshold the fan which is another component will be switched on to cool down the temperature. If the temperature is lower than the threshold the bulb will be switched on to rise the temperature. All the status report of the system will be given send to famers phone by using the GSM module. Throughout the process of monitoring the health of silk worm always had a front foot. Cause one diseased worm can make another worm ill. Hence, to avoid this a disease detection system which will detect diseases silk worm will help farmers. For doing so CNN and Image processing algorithms are used for disease detection on time This model will classify the diseased silkworm in different diseases based on which it is suffering from. CNN is trained with its auto generated features. An average accuracy of 85%, 75% and 59% for classification of healthy and diseased silkworms.