RESTful Web Service integration using Android platform

Bohara, Mohammed Husain; Mishra, Madhuresh; Chaudhary, Sanjay

doi:10.1109/icccnt.2013.6726550

Cited by 12 publications

(7 citation statements)

References 9 publications

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“…SOA mendukung berbagai karakteristik untuk membangun model berbasis broker yang dikenal sebagai SOA 1.0. [13].…”

Section: Pendahuluanunclassified

“…Teknologi yang digunakan untuk mengembangkan layanan web dan untuk berkomunikasi dengan layanan dikenal sebagai Representational State Transfer, atau disingkat REST. Kelebihan yang REST daripada web service lainnya adalah: a. Ligh-weight [13], [16]: Tidak adanya enkripsi atau deskripsi overhead baik dalam permintaan HTTP maupun pesan respons adalah yang membuat REST memiliki reputasi yang ringan. b.…”

Section: Restfullunclassified

“…b. Simplicity [13], [16]: REST secara signifikan lebih mudah digunakan karena fakta bahwa itu tidak memerlukan deklarasi antarmuka apa pun seperti yang dilakukan layanan web lainnya.…”

Section: Restfullunclassified

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Implementasi RESTful untuk Mengurangi Mean Time to Resolve pada Alert Handling

Aditya

Rachmat²,

Harika³

et al. 2022

Jur. Ris. Kom.

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One of the responsibilities of the company's IT infrastructure team is ensuring that IT services or services stay available. One part of analyzing the performance of IT infrastructure is MTTR (Mean Time to Resolve) or the average time necessary to restore a service that is experiencing issues. Warnings or alerts are shown when a service is encountering difficulties. As a member of the IT infrastructure team, the on-call engineer is responsible for managing alarms. At PT Sense Health Indonesia, difficulties manifest in the form of recurrence alerts, or warnings resulting from previously fixed or rectified issues. This warning is repeated with sufficient frequency to enhance the MTTR value. The findings demonstrated that the integration of tools using the RESTful approach streamlined the process of processing alerts. The deployment led to a 78% decrease in the average time required to handle alarms. This study contributes by demonstrating one method for decreasing MTTR for alert handling

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“…SOA mendukung berbagai karakteristik untuk membangun model berbasis broker yang dikenal sebagai SOA 1.0. [13].…”

Section: Pendahuluanunclassified

Section: Restfullunclassified

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Implementasi RESTful untuk Mengurangi Mean Time to Resolve pada Alert Handling

Aditya

Rachmat²,

Harika³

et al. 2022

Jur. Ris. Kom.

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“…During literature survey, we found existing Agro Advisory systems like eSagu [6], Agrisnet [7], Kissan Kerela [8], aAqua [9], mKrishi [10], lIT Mumbai's Agro Advisory System [11] and Krishimantra [3][4][5] Ontology based Agro Advisory system is developed by lIT Mumbai which is available for farmers to pose their queries to the system and getting the best solution to their problems. In ontology, concepts are elaborated with soil and climate conditions for cotton, varieties of cotton, diseases affecting cotton, cure for these diseases, pests affecting cotton, and their precaution and cure.…”

Section: R Elated W Orkmentioning

confidence: 99%

Agro advisory system for cotton crop

Chaudhary

Bhise

Banerjee

et al. 2015

2015 7th International Conference on Communication Systems and Networks (COMSNETS)

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In the agricultural domain, the main challenge is to present the new information and research to the farmers so that they can leverage the power of ICT to improve their agricultural practices and thereby the production. Huge amount of agriculture related data like weather data, soil health records, cropping pattern, location specific crop disease and pest are collected from different sources like services, remote satellites, and network of sensors. An agro advisory system presented in this paper helps to bridge the gap between farmers and the agriculture domain experts and developed for the cotton farmers in Gujarat region of India. The system consists of three basic components; Cotton Ontology, Web Services, and Mobile Application Development. The cotton ontology maintains domain knowledge required for answering farmer queries. The ontology contains information regarding crop, soil, cultivation process, disease, pest, and other relevant information. Protege ontology development tool is used to develop this ontology. Appropriate web services were built which help interactions with different data sources. The RESTful web services are programmed in Java using the JAX-RS/Jersey API and the Eclipse EE IDE. The services are developed and deployed on a cloud based application server provided by Heroku. The web services are invoked from the mobile device and in turn they connect to various data sources like Open Weather API, SQL database and the Ontologies. The farmers can use this application based on very simple android mobile interfaces. The prototype is developed using Java, Android SDK -v14 and Eclipse IDE.

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“…Cotton production is directly responsible for the livelihood of 60 million individuals, including 4.5 million farmers [5]. Keeping in mind all the factors stated above for the cultivation of cotton, conclusion can be inferred as the cotton is highly volatile in nature.…”

Section: Introductionmentioning

confidence: 99%

An AI Based Web Portal for Cotton Price Analysis and Prediction

Bohara¹,

Patel²,

Patel³

et al. 2021

Atlantis Highlights in Computer Sciences

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Artificial Intelligence based Web portal is extensively used in worldwide because it used to solve various primary low level problems in agriculture such as predicting precise prices of agriculture product using machine learning algorithms, enabling direct connection between buyer and seller without any middlemen, decreasing wastage of post-harvest crop, fixing appropriate price margin for farmers and so on. These steps helps to increase the capital income and creates the beneficial changes in the agriculture and also it leads to take the agriculture to next level. Cotton is a crop that is possibly the most expensive including all agricultural products sold. Owing to the high uncertainty of cotton markets, it is incredibly difficult to forecast future demand patterns and develop an acceptable pricing plan in order to compete in the market and maximize the company's volume for long-term development. Keeping in mind all the factors stated above for the cultivation of cotton, conclusion can be inferred as the cotton is highly volatile in nature. In this paper, we tend to build an Artificial Intelligence based Web Portal which provides data analysis of price of past years and also gives predictions about the cotton prices to the fellow traders. The paper aims to create a web model for cotton price prediction. Furthermore, the study tries to run a multiple regression model based on different variables to estimate the price of cotton.

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RESTful Web Service integration using Android platform

Cited by 12 publications

References 9 publications

Implementasi RESTful untuk Mengurangi Mean Time to Resolve pada Alert Handling

Implementasi RESTful untuk Mengurangi Mean Time to Resolve pada Alert Handling

Agro advisory system for cotton crop

An AI Based Web Portal for Cotton Price Analysis and Prediction

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