Development of an asynchronous communication channel between wireless sensor nodes, smartphone devices, and web applications using RESTful Web Services for intelligent farming
Environment and agriculture related applications have been gaining ground for the past several years and have been the context for researches in ubiquitous and pervasive computing. This study is a part of a bigger study that uses artificial intelligence in developing models to detect, monitor, and forecast the spread of Fusarium oxysporum cubense TR4 (FOC TR4) on Cavendish bananas cultivated in the Philippines. To implement an Intelligent Farming system, 1) wireless sensor nodes (WSNs) are deployed in Philippine banana plantations to collect soil parameter data that is considered to affect the health of Cavendish bananas, 2) a custom built smartphone application is used for collecting, storing, and transmitting soil data, plant images and plant status data to a cloud storage, and 3) a custom built web application is used to load and display results of physico-chemical analysis of soil, analysis of data models, and geographic locations of plants being monitored. This study discusses the issues, considerations, and solutions implemented in the development of an asynchronous communication channel to ensure that all data collected by WSNs and smartphone applications are transmitted with a high degree of accuracy and reliability. From a design standpoint: standard API documentation on usage of data type is required to avoid inconsistencies in parameter passing. From a technical standpoint, there is a need to include error-handling mechanisms especially for delays in transmission of data as well as generalize method of parsing thru multidimensional array of data. Strategies are presented in the paper.
Paulo Lim, John Noel C. Victorino, Jerelyn Co, Ivan Lester Saddi, Sharlene Mae Paelmo, Bon Lemuel Dela Cruz, "Development of an asynchronous communication channel between wireless sensor nodes, smartphone devices, and web applications using RESTful Web Services for intelligent farming," Proc. SPIE 10444, Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017), 1044405 (6 September 2017); https://doi.org/10.1117/12.2279020