The sensor technology is getting advanced day by day in terms of facilitating human in different aspects of human life. The one of the major constraints on the wireless sensor nodes is the battery embedded on them. As these batteries are irreplaceable, the routing to preserve the energy of the sensor nodes becomes prominent. The cluster-based routing has not only acquired network longevity but also has helped in the energy balancing in the network. But, Cluster Head (CH) selection is NP (Nom-Polynomial)-hard problem therefore, in this paper, we have proposed Enhanced Stable Routing Algorithm (ESRA) for Heterogeneous Wireless Sensor Network (HWSN). The CH selection is enhanced by involving the distance factor in the threshold formula. While doing so, the energy consumption is reduced, and stability period is enhanced significantly. It is observed that through the simulation in MATLAB, the stability period by ESRA is enhanced by 15.43%, 64.39% and network lifetime by 30.95%, 73.16% as compared to P-SEP and DSEP protocols, respectively.

With the growing needs of Agriculture sector, the farmers and stakeholders need to make important decisions influenced by various factors like soil type, pollution level, humidity, temperature, rainfall, geographic attributes etc. This paper deliberates about the various data mining techniques that analyze the environmental factors that affect the agricultural parameters. These techniques give solution to various decision making problems faced by the agriculture sector today. In this paper we focus on optimizing effect of weather on agriculture using various techniques like Correlation Analysis, multidimensional modeling, k-means, ANN, SVM, KG classification, PAM, CLARA, DBSCAN etc. This information can help our farmers to increase their production based on the behavior of the climate of their location.