A low-cost versatile system for continuous real-time respiratory activity measurement as a tool in environmental research

Djerdj, Tamara; Peršić, Vesna; Hackenberger, Davorka K.; Hackenberger, Domagoj K.; Hackenberger, Branimir K.

doi:10.1016/j.measurement.2021.109928

Cited by 3 publications

(1 citation statement)

References 32 publications

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“…The language in which the application was developed was Python. This language has a vast library of ready-made functions and extensive literature to support it [25][26][27]. It provided us with a great arsenal to perform data analysis in many possible ways.…”

Section: Calculation Of the Normalized Performance Index (Pi)mentioning

confidence: 99%

A Mobile Application to Follow Up the Management of Broiler Flocks

et al. 2021

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Broiler meat is one of the most consumed meats worldwide. The broiler production system poses several challenges for the producer, including maintaining environmental conditions for rearing. The popularization of mobile devices (smartphones) among people, including those with lower incomes, makes it possible for specialist systems to be developed and used for diverse purposes through Apps (mobile application). The present study proposed the development of a mobile application to help farmers follow up on-farm flock management. We retrieved rearing environment and flock data from commercial broiler farms that complied with broiler-producing standards and followed the breeders’ recommendations. Data were organized and normalized to serve as the basis for the software. We specified a performance index based on the average environment and flock-based data. The language used for the application development was Python compatible with the GNU GPL (General Public License), which has a vast library of ready-made functions. For the graphical interface, we selected Kivy and KivyMD framework. The developed mobile application might help farmers evaluate broiler rearing conditions on-farm during the flock’s growth and grade the flock using a performance index.

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Section: Calculation Of the Normalized Performance Index (Pi)mentioning

confidence: 99%