Articles
Multi-agent based context aware information gathering for agriculture using WMSN
Bhanu KN et al., Egyptian Informatics Journal, 2019
Multi-agent based context-aware information gathering is used in Wireless multimedia sensor networks (WMSN) to monitor agriculture. Context -aware information gathering helps in conserving the energy of sensor nodes in the sensor network so as to prolong the lifetime of sensor networks. Three kinds of contexts are considered here for detecting emergency, temporal and computational contexts that helps in interpretation of soil parameters along with detection of diseased plants, weeds and fire in agricultural fields.
Access this article at: https://doi.org/10.1016/j.eij.2018.07.001
IoT based Smart System for Enhanced Irrigation in Agriculture
Bhanu KN et al., ICESC, 2020
Innovation in Internet of Things (IoT) has made changes in everyday life. Agriculture plays a major role in most of the countries and there is a need for this sector is to become "Smart". The key parameters that can be considered for better growth of crops are soil types, soil moisture, mineral nutrients, temperature, light, oxygen and so on. Some of these parameters are considered for data analysis that enables farmers to take better agricultural decisions.
Access this article at: https://ieeexplore.ieee.org/abstract/document/9156026
Machine learning Implementation in IoT based Intelligent System for Agriculture
Bhanu KN et al., INCET, 2020
Agriculture provides a rich source of parameters for data analysis which helps in better yielding of crops. The usage of IoT devices in agriculture helps in the information gathering that enables smart farming. Implementation of Machine learning on agricultural data acquired from IoT helps the farmers to take appropriate decisions that helps in better crop yield.
Access this article at: https://ieeexplore.ieee.org/abstract/document/9153978
Farm Vigilance: Smart IoT System for Farmland and Animal Intrusion Monitoring using Neural Network
Bhanu KN et al., ASIANCON , 2021
Connecting all the electronic devices through internet have given rise to an era of Internet of Things (IoT). As an enhancement to this, machine learning can be performed on data acquired from IoT on cloud. Data so acquired can be used to automate the ongoing activities on farmland such as irrigation and animal intrusion detection that helps farmers take better decision and yield better crops.
Access this article at: https://ieeexplore.ieee.org/abstract/document/9544926