Saraswathi Sivamani

A Smart Service Model Based on Ubiquitous Sensor Networks Using Vertical Farm Ontology

Application of the technology systems is growing in various fields and the agriculture is not an exception. Agriculture is also reaping the benefits of technological innovation which helps in quantitative and qualitative food production. Vertical farm, one of the agricultural practices, is considered to be the future of agriculture with the rate of population migrating into urban areas. Ubiquitous computing in agriculture is emerging remarkably in this fast processing pervasive environment, owing to wireless sensor network (WSN). Building a context aware system for the vertical farm is complex without the semantic interoperability between the Internet of things (IOT). In this paper, we propose a vertical farm ontology (VFO), an OWL based ontology model which helps in more understanding of the relationship between the domain factors. With the proposed model, the information from the Internet of things is recomposed as context information and made understandable for the other systems. For the sake of agriculture, we hope that our proposed model will pave great path for the development of smart and intelligent agricultural services.

A Study on Intelligent User-Centric Logistics Service Model Using Ontology

Much research has been undergone in the smart logistics environment for the prompt delivery of the product in the right place at the right time. Most of the services were based on time management, routing technique, and location based services. The services in the recent logistics environment aim for situation based logistics service centered around the user by utilizing various information technologies such as mobile devices, computer systems, and GPS. This paper proposes a smart logistics service model for providing user-centric intelligent logistics service by utilizing smartphones in a smart environment. We also develop an OWL based ontology model for the smart logistics for the better understanding among the context information. In addition to basic delivery information, the proposed service model makes use of the location and situation information of the delivery vehicle and user, to draw the route information according to the user’s requirement. With the increase of internet usage, the real-time situations are received which helps to create a more reliable relationship, owing to the Internet of Things. Through this service model, it is possible to engage in the development of various IT and logistics convergence services based on situation information between the deliverer and user which occurs in real time.

An OWL-Based Ontology Model for Intelligent Service in Vertical Farm

Recently, the agriculture is undergoing a technical drift in both innovation and technology. As a result, we have vertical farming which helps to increase the rate of food production tremendously, with the appropriate environmental factors in middle of the urban areas. Many researches have been undergone in the agricultural environment, which mainly focused on the smart services in the u-agriculture environment. Ubiquitous computing is one of the major developing technology in this fast evolving pervasive environment. Building a context aware system for the vertical farm is still complex without the shared understanding of the domains which can also be referred as set of entities, relations, functions and services. To resolve this issue, we propose the OWL based ontology model which defines the relationship between the domain factors that helps in both monitoring and controlling services of vertical farm. We have classified the basic concepts for the vertical farm environment which can be extended according to the domain of interest.

A Rule Based Event-Driven Control Service for Vertical Farm System

In this paper, we have discussed the algorithmic approach of rule-based control selector in the automatic vertical farm system. Many researches have been undergone in the automation process to scale down the human labor for the creation of a crop’s ideal environment to reap agriculture benefits for farmers. In an automated environment, analyzing and choosing the right controller takes the main priority. Especially in a mass crop production system where different crops are cultivated at the same time, selecting an appropriate controller has to be handled carefully to avoid any mishaps. In this selection process, factors such as weather and crop’s growth condition are considered and evaluated accordingly. With the help of ontology, Semantic Web Rule Language (SWRL) rules are written for the selection of controller for each sector which in turn has selected crops. The flow of the Control selection involves four basic steps such as identifying, matching, rating and selecting.

A smart service model in greenhouse environment using event-based security based on wireless sensor network

In the smart agricultural environment such as greenhouse or vertical farm, the automation process is performed using the environment sensors to maintain the growth of the crops. Currently, the system rely on the defined rule to perform automation, but the situation can turn catastrophic. With the interruption in the communication, data forging, or eavesdropping, the crops will be rotten and destroyed. Therefore, to maintain the automation without failure, the connection needs to be secure and tampering has to be avoided. In this paper, we discuss the security solution for the wireless sensor networks in the automated agricultural environment without any human intervention. The sink node that collects the sensor values organizes the data and transfer the data to the server, along with the XML encryption and private key mechanism for the communication. The secure protocol is used to make connection using the private key, XML ecryption prevents the system from eavesdropping, and forging. Some of the events discussed in the papers are EVNData, SENSORError, DDoSAttack, and ConnThreat. With the help of the event and the tag information, the data security and confidentiality is increased, for the better automation and crop growth.

A service model for nutrition supplement prediction based on Fuzzy Bayes model using bigdata in livestock

The paper proposes a novel method in the decision support system for the nutritional management of livestock using the Bayesian model based on fuzzy rules. The objective is to analysis the decision based on fuzzy rules over the nutrition management that helps to improve the health of the livestock. Bayesian logic mainly focuses on the probabilities of the food intake with respect to the Food Intake Amount, Cow Stage and weight of the livestock. The conditional probability of the Bayesian reasoning is introduced along with the fuzzy rule, to determine the health status of the livestock. The fuzzy logic technique helps to decide on the decision system, when there are more than one dependencies. In this paper, the total digestible nutrient of the cow is determined over the period of time to get the rate of probability, and the fuzzy rule is applied to determine the health status of the cow, to predict the nutritional intake in the livestock.

An Android-Based Feed Behavior Monitoring System for Early Disease Detection in Livestock

The objective of this study was to develop an android based mobile application to analyze and prevent the possible disease in the early stage by monitoring the feeding behavior of the livestock. The proposed system secures the information such as feed intake, feeding time, rumination and the feeding rate through the Internet of Things equipped in the livestock farm. Every day feed intake and the feed intake rate are compared with the earlier day, a week before and a month before to find the tardiness or other possible disease in the livestock and an alert is sent to the farmers as text and as well as shown in the mobile application for immediate response. The proposed system is expected to contribute the enhancement of the productivity in the livestock farm, by preventing the disease at its early stage.

Context-Aware Control Service Model Based on Ontology for Greenhouse Environment

IT fusion service of every kind is having the limelight in various fields lately. Agriculture area which inevitable in development of human civilization is also trying development of various IT fusion service, and the method that efficiently cultivates various crops with automatic control as an example of these service. However, most of these services have weakness that intervention of human is inevitable for exception with various variables. Therefore, this thesis proposes ontology based context aware environment control service model that could actively deal with exceptions that could happen in actual greenhouse cultivation environment without human intervention by defining relationship between each environmental factors and control factors by utilizing ontology.