Smart agriculture management system using internet of things

In the world of digital era, an advance development with internet of things (IoT) were initiated, where devices communicate with each other and the process are automated and controlled with the help of internet. An IoT in an agriculture framework includes various benefits in managing and monitoring the crops. In this paper, an architectural framework is developed which integrates the internet of things (IoT) with the production of crops, different measures and methods are used to monitor crops using cloud computing. The approach provides real-time analysis of data collected from sensors placed in crops and produces result to farmer which is necessary for the monitoring the crop growth which reduces the time, energy of the farmer. The data collected from the fields are stored in the cloud and processed in order to facilitate automation by integrating IoT devices. The concept presented in the paper could increase the productivity of the crops by reducing wastage of resources utilized in the agriculture fields. The results of the experimentation carried out presents the details of temperature, soil moisture, humidity and water usage for the field and performs decision making analysis with the interaction of the farmer

Design of optimal search engine using text summarization through artificial intelligence techniques

Natural language processing is the trending topic in the latest research areas, which allows the developers to create the human-computer interactions to come into existence. The natural language processing is an integration of artificial intelligence, computer science and computer linguistics. The research towards natural Language Processing is focused on creating innovations towards creating the devices or machines which operates basing on the single command of a human. It allows various Bot creations to innovate the instructions from the mobile devices to control the physical devices by allowing the speech-tagging. In our paper, we design a search engine which not only displays the data according to user query but also performs the detailed display of the content or topic user is interested for using the summarization concept. We find the designed search engine is having optimal response time for the user queries by analyzing with number of transactions as inputs. Also, the result findings in the performance analysis show that the text summarization method has been an efficient way for improving the response time in the search engine optimizations

An energy-efficient cluster head selection in wireless sensor network using grey wolf optimization algorithm

Clustering is considered as one of the most prominent solutions to preserve theenergy in the wireless sensor networks. However, for optimal clustering, anenergy efficient cluster head selection is quite important. Improper selectionofcluster heads(CHs) consumes high energy compared to other sensor nodesdue to the transmission of data packets between the cluster members and thesink node. Thereby, it reduces the network lifetime and performance of thenetwork. In order to overcome the issues, we propose a novelcluster headselection approach usinggrey wolf optimization algorithm(GWO) namelyGWO-CH which considers the residual energy, intra-cluster and sink distance.In addition to that, we formulated an objective function and weight parametersfor anefficient cluster head selection and cluster formation. The proposedalgorithm is tested in different wireless sensor network scenarios by varyingthe number of sensor nodes and cluster heads. The observed results conveythat the proposed algorithm outperforms in terms of achieving better networkperformance compare to other algorithms

An effective identification of crop diseases using faster region based convolutional neural network and expert systems

The majority of research Study is moving towards cognitive computing, ubiquitous computing, internet of things (IoT) which focus on some of the real time applications like smart cities, smart agriculture, wearable smart devices. The objective of the research in this paper is to integrate the image processing strategies to the smart agriculture techniques to help the farmers to use the latest innovations of technology in order to resolve the issues of crops like infections or diseases to their crops which may be due to bugs or due to climatic conditions or may be due to soil consistency. As IoT is playing a crucial role in smart agriculture, the concept of infection recognition using object recognition the image processing strategy can help out the farmers greatly without making them to learn much about the technology and also helps them to sort out the issues with respect to crop. In this paper, an attempt of integrating kissan application with expert systems and image processing is made in order to help the farmers to have an immediate solution for the problem identified in a crop

Cost-effectiveness of interventions to control cardiovascular diseases and type 2 diabetes mellitus in South Asia: protocol for a systematic review.

INTRODUCTION: While a number of strategies are being implemented to control cardiovascular diseases (CVDs) and type 2 diabetes mellitus (T2DM), the cost-effectiveness of these in the South Asian context has not been systematically evaluated. We aim to systematically review the economic (cost-effectiveness) evidence available on the individual-, group- and population-level interventions for control of CVD and T2DM in South Asia. METHODS AND ANALYSIS: This review will consider all relevant economic evaluations, either conducted alongside randomised controlled trials or based on decision modelling estimates. These studies must include participants at risk of developing CVD/T2DM or with established disease in one or more of the South Asian countries (India, Bangladesh, Pakistan, Sri Lanka, Nepal, Maldives, Bhutan and Afghanistan). We will identify relevant papers by systematically searching all major databases and registries. Selected articles will be screened by two independent researchers. Methodological quality of the studies will be assessed using a modified Drummond and a Phillips checklist. Cochrane guidelines will be followed for bias assessment in the effectiveness studies. RESULTS: Results will be presented in line with the PRISMA (Preferred Reporting Items for Systematic review and Meta-analysis) checklist, and overall quality of evidence will be presented as per the GRADE (Grades of Recommendation, Assessment, Development and Evaluation) approach. ETHICS AND DISSEMINATION: The study has received ethics approval from the All India Institute of Medical Sciences, New Delhi, India. The results of this review will provide policy-relevant recommendations for the uptake of cost-effectiveness evidence in prioritising decisions on essential chronic disease care packages for South Asia. STUDY REGISTRATION NUMBER: PROSPERO CRD42013006479

Periosteum-Augmented Soft-Tissue Graft for Anterior Cruciate Ligament Reconstruction

Soft-tissue grafts are an option for anterior cruciate ligament reconstruction. One of the major drawbacks of soft-tissue grafts is the delay in the osteointegration and ligamentization of the implanted graft. Enveloping the ends of the graft with periosteum sleeves can hasten the osteointegration process and help in quicker rehabilitation of the patient. This article describes a simple and unique way to augment the soft-tissue graft with periosteum for anterior cruciate ligament reconstruction