Aaron U. Aquino, Dustin G. Baylon, Francis Paul B. Dela Cruz, Ma. Armae Hazel Joy M. Medina, Girlie A. Reyes, Jascha Mae L. Tulauan, Timothy M. Amado, J. M. Ramos, L. K. Tolentino, E. Fernandez
{"title":"基于物联网和树莓派模块的太阳能闭环蠕虫堆肥系统的开发","authors":"Aaron U. Aquino, Dustin G. Baylon, Francis Paul B. Dela Cruz, Ma. Armae Hazel Joy M. Medina, Girlie A. Reyes, Jascha Mae L. Tulauan, Timothy M. Amado, J. M. Ramos, L. K. Tolentino, E. Fernandez","doi":"10.1109/HNICEM48295.2019.9073372","DOIUrl":null,"url":null,"abstract":"Vermicomposting is a low-cost technology that naturally converts organic wastes into organic fertilizers, commonly called vermicompost, through the combined action of earthworms and mesophilic microorganisms. Vital parameters, such as moisture and temperature, must be considered in the vermicompost production to achieve optimum yield. However, manual monitoring and correction of these said parameters do not give guaranteed results. Also, the traditional process of harvesting vermicompost consumes longer time and requires more human intervention. As a solution, the proponents introduced the development of a system which monitors and corrects these vital parameters, determines the readiness of vermicompost for harvest using digital image processing, and automatically sieves the vermicompost. The system uses Raspberry Pi microcontroller, sensors, and an android phone for monitoring. To measure the system’s reliability and efficiency, the proponents conducted two setups of vermicomposting system – one controlled and the other uncontrolled. From the data gathered, the automated system surpassed the latter in terms of production time, yield quality and quantity.","PeriodicalId":6733,"journal":{"name":"2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )","volume":"18 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Development of a Solar-Powered Closed-Loop Vermicomposting System with Automatic Monitoring and Correction via IoT and Raspberry Pi Module\",\"authors\":\"Aaron U. Aquino, Dustin G. Baylon, Francis Paul B. Dela Cruz, Ma. Armae Hazel Joy M. Medina, Girlie A. Reyes, Jascha Mae L. Tulauan, Timothy M. Amado, J. M. Ramos, L. K. Tolentino, E. Fernandez\",\"doi\":\"10.1109/HNICEM48295.2019.9073372\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vermicomposting is a low-cost technology that naturally converts organic wastes into organic fertilizers, commonly called vermicompost, through the combined action of earthworms and mesophilic microorganisms. Vital parameters, such as moisture and temperature, must be considered in the vermicompost production to achieve optimum yield. However, manual monitoring and correction of these said parameters do not give guaranteed results. Also, the traditional process of harvesting vermicompost consumes longer time and requires more human intervention. As a solution, the proponents introduced the development of a system which monitors and corrects these vital parameters, determines the readiness of vermicompost for harvest using digital image processing, and automatically sieves the vermicompost. The system uses Raspberry Pi microcontroller, sensors, and an android phone for monitoring. To measure the system’s reliability and efficiency, the proponents conducted two setups of vermicomposting system – one controlled and the other uncontrolled. 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Development of a Solar-Powered Closed-Loop Vermicomposting System with Automatic Monitoring and Correction via IoT and Raspberry Pi Module
Vermicomposting is a low-cost technology that naturally converts organic wastes into organic fertilizers, commonly called vermicompost, through the combined action of earthworms and mesophilic microorganisms. Vital parameters, such as moisture and temperature, must be considered in the vermicompost production to achieve optimum yield. However, manual monitoring and correction of these said parameters do not give guaranteed results. Also, the traditional process of harvesting vermicompost consumes longer time and requires more human intervention. As a solution, the proponents introduced the development of a system which monitors and corrects these vital parameters, determines the readiness of vermicompost for harvest using digital image processing, and automatically sieves the vermicompost. The system uses Raspberry Pi microcontroller, sensors, and an android phone for monitoring. To measure the system’s reliability and efficiency, the proponents conducted two setups of vermicomposting system – one controlled and the other uncontrolled. From the data gathered, the automated system surpassed the latter in terms of production time, yield quality and quantity.