Real time multi view image based FPC plant management with SS data security and low rate attack detection for efficient smart agriculture in WSN

Abstract

The problem of smart agriculture has been well studied and the security in Wireless Sensor Networks (WSN) has been analyzed in detail. There are a number of approaches discussed in the literature to support the growth of agriculture by considering different factors. But still the performance of plant management is not up to the expected level in terms of plant management and security concern. To handle these issues, an efficient multi view image based plant management technique which consider color and contrast features to obtain the features of fluid, plant, climate to compute different supportive measures like Fluid Specific Growth Support (FSGS), Plant Specific Growth Support (PSGS) and Climate Specific Growth Support (CSGS) measures to compute the value of Plant Growth Measure (PGM) and Crop Yield Measure (CYM). Also, using the same support measures, the presence of diseased plants is identified and fertilizers are regulated accordingly. Similarly, the wireless sensor network has been used as monitoring environment which has several routes to monitor different locations of agriculture lands. The presences of different routes are monitored for the transmission of different agriculture data. To handle the security issues, a low rate attack detection scheme is presented which finds the routes and for each route the method computes Service centric Legitimate Support (SCLS) to find low rate attacks. Similarly, the data security by controlling different smart devices in agriculture lands is enforced by using service centric data encryption (SCDE) scheme which uses different encryption scheme and keys to encrypt the data being used for controlling the devices of agricultural lands. The proposed method improves the performance of smart agriculture and improves the data security with higher low rate detection accuracy.