B. Siva Kumar's research while affiliated with SRM Institute of Science and Technology and other places

In the recent past, the agriculture and farming industry has become the precision network connectivity of sensors with a new dimension of Internet of Things (IoT) technology. The cloud computing and wireless sensor network‐ (WSN) based extensive distance network in IoT can be applied to the agriculture and farming industry in a remote area. In this paper, we propose scalable wireless sensor network architecture for monitoring and control using IoT for agriculture and farming in a remote area. One of the significant managements in precision agriculture and farming (PAF) is water resource irrigation and proper utilization of water resources. Appropriate utilization of water irrigation management can be achieved by applying WSN technology using IoT. The efficient communication of various wireless sensors is processed using IoT in PAF to improve the productivity of farmers. We have analyzed the WSN structure based on throughput maximization, latency minimization, high signal‐to‐noise ratio (SNR), minimum mean square error, and improved coverage area. The experimental results have proved that the proposed methodology provides better performance than conventional IoT‐based agriculture and farming.

Constituting the agriculture solid substance manufacture, the post-harvest sector processing schema is direct to preventing reduce the losses in intelligent agriculture. Many processing schemata will be preventing post-harvest losses on the agriculture solid substance manufacture, especially sekai-ichi apple is the regularly used fruit also used to make active in human-related activities of the sensory and control function consisting of an agricultural industry. Sekai-ichi apple is being a definite number of diseases induce, but it is to the highest degree of wastage involving in the Post-Harvest process. Especially sekai-ichi apple count loss is an unsafe many time because it not critically post-harvest. Regardless of consideration, the existing hierarchical model specified post-harvest losses prevention research has deficiencies to precise and quick detection of wastage for ensuring healthy separation of agriculture surroundings. This paper suggests a “Hierarchical Model within Ontology Enabled IoT” for distinguishable healthy separation of sekai-ichi apple by using Boosted Continuous Non-spatial whole Attribute Extraction (BCNAE). Sekai-ichi apple count loss is always safe on critically post-harvest. Proposed Post-Harvest hierarchical model specified post-harvest losses prevention and deficiencies to precise and quick detection of wastage for ensuring healthy separation of agriculture surroundings. In these suggestions, the separation cognitive operation takes the three levels of processing schemes such as lower level, middle level, and higher level. Firstly, the lower level is express agreements with the dynamic functioning for maintaining the definite number of manual induces. This lower level showing an absorption with the activity of manual separation by the human reliability determination. Secondly, the middle level is an express arrangement with the dynamic functioning for reducing the overfitting and accommodate to fitting the right shape deliberation. Middle level is establishing being generalized by concentrating the time-varying features in the occurrence of a change for the worse identification. Finally, the upper level is express for features refining with the help of the function of sekai-ichi apple image segmentation connection. This interpretability process helps to make the proven position of a prominent classification in a particular fruit on the agriculture solid substance. These three processing flow constructs the ontology structure with manually collected sekai-ichi apple images from a 3D sensor. The observational consequences express that the proposed BCNAE framework recognizes a detection performance carrying out with an optimized—separation ratio for time-variant of the separation process.