Cotton is an essential commercial crop. Unfortunately, this crop is affected by many pests and diseases, which can cause considerable loss in yield. Climate has a strong correlation with the occurrence of pests and diseases in crops. Currently, weather forecasting services are available to the farmers, which help with weather-based planning of farm operations. Still, weather-based pest and disease forewarning services are not available to all the farmers. Unfortunately, cotton cultivation consumes about one-third of total pesticide consumption, which increases the cost of production apart from polluting the environment. An information and communication technology (ICT) based intelligent pest and disease forewarning system for cotton is an innovative system for providing forewarning on pests and diseases. It aims at improving farm productivity through better crop management. In this paper, the proposed method aims to predict the occurrence of pests and diseases based on microclimatic parameters. This pest and disease forewarning information and appropriate crop management practices will be disseminated to the farmers using electronic media through short message service (SMS), the Internet, etc. In this way, both livelihood security and environmental security are achieved. The proposed model shows a higher optimal performance then the two related works in terms of the average root mean square error rate, average accuracy rate, average percentage error rate, and prediction accuracy.

Vehicular ad hoc network (VANET) is an emerging trend where vehicles communicate with each other and possibly with a roadside unit. Collaboration among vehicles is significant in VANET. Resource constraint is one of the great challenges of VANETs. Owing to the absence of centralised management, there is pitfall in optimal resource allocation that leads ineffective routing. Effective reliable routing is quite essential to achieve intelligent transportation. Stochastic dynamic programming (SDP) is currently employed as a tool to analyse and solve network resource constraint and allocation issues of resources in VANET. The authors have considered this work as a geographic angular zone‐based two‐phase dynamic resource allocation problem with homogeneous and heterogeneous resource class. This work uses relaxed approximation‐based SDP algorithm to generate optimal resource allocation strategies over time in response to past task completion status history. The second‐phase resource allocation uses the observed outcome of the first‐phase task completion to provide optimal viability decisions. They have also suggested an alternative solution called model predictive control algorithm (MPCA) that used approximation as a part to allocate resource over time in response to information on data transmission completion status. Simulation results show that the proposed schemes works significantly well for homogeneous resources.

In Vehicular Adhoc Networks (VANETs), collaboration and coordination between mobile nodes (vehicles) and static nodes (roadside infrastructure) are significant. The great challenges of the VANETs are rapid changes of topology, perceiving and transmitting of physical environment parameters. Because of the lack of central coordinator and the selfishness of the vehicles, effective routing is a challenging task in VANETs. Optimal resource allocation is quite essential to achieve an effective routing. Game theoretical models have currently used as a tool bring fairness among the resources utilization and users. This work proposes an approximation Colonel Blotto Game (CBG) model to analyse the possible strategy set for each player in allocating resources. We have calculated the payoff to nodes for motivating the players those who are involved in the routing process. A generalization of CBG has enabled to derive deterministic and implementable equilibrium strategies. The existence of Nash equilibrium (NE) for pure strategy has proven. The proposed work has also found out the optimal strategies by introducing a method of Lagrange multipliers. Experimental results show that the proposed CBG based resource allocation scheme could significantly allocate the resources fairly to forward the packet thereby it enhances the routing.