Performance Analysis of Android-Based Smart Agriculture Monitor and Control Applications

  • Helmy Politeknik Negeri Semarang
  • Fenny Rahmasari Politeknik Negeri Semarang
  • Arif Nursyahid Politeknik Negeri Semarang
  • Thomas Agung Setyawan Politeknik Negeri Semarang
  • Ari Sriyanto Nugroho Politeknik Negeri Semarang
Keywords: Android Application, Performance Analysis, IoT, Smart Agriculture


The ever-evolving digital era leads to an industrial revolution in the internet of things (IoT)-based smart agriculture and smart farm. Of many uses is the use of an Android-based app that monitors and controls parameters in the cultivation process in this digital era. An unstable internet connection can interfere with the monitoring process. For this reason, a system integration into a single app running even in an offline condition is needed; therefore, the user can monitor and control the Android-based smart agriculture app in two modes, namely online and offline. A performance analysis is also necessary to know the app's reliability in sending and receiving data. This system integration used two modes of operation, i.e. online and offline, wherein the online mode, the app will communicate with the server when connected with the internet using representational state transfer application programming interface (REST API). Meanwhile, the app will communicate directly with the system through a local access point in the offline mode. This app interacts with the system with the MQTT protocol where the app acts as an MQTT client. The performance analysis was conducted in the black box test, load activity test, and app performance test from the Android profiler. The acquired test from the app functionality test (black box) showed that the user could monitor and control the smart agriculture in online and offline mode through the app. The average load time for all the activities was 3.507 seconds with a network bandwidth of 4.54 Mbps. At the same time, the average load time in a network bandwidth of 35.35 Mbps was 1.4 seconds. The system performance test indicated the app was relatively light as the CPU usage for the app was 31%, with a memory usage of 453.8 MB.


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How to Cite
Helmy, Fenny Rahmasari, Arif Nursyahid, Thomas Agung Setyawan, & Ari Sriyanto Nugroho. (2022). Performance Analysis of Android-Based Smart Agriculture Monitor and Control Applications. Jurnal Nasional Teknik Elektro Dan Teknologi Informasi, 11(1), 23-30.