摘要：Greenhouse is a very effective method of matching and has been able to contribute to food independence in various countries. Plants that are in the greenhouse must be maintained with chemical-physical parameters in order to grow optimally. Monitoring of plants in greenhouses must always be done. Some monitoring reports have been made online so that they can provide solutions as quickly as possible if there is a disturbance on the plants. Unfortunately, online monitoring is still dependent on internet networks that require network infrastructure needs that have many limitations. As a result, many agricultural lands are not covered by the internet network to monitor the greenhouse. The use of a large number of sensor nodes also affects the decline in available broadband internet performance so as to reduce monitoring performance. In this research proposed a fog network that connects the sensor node with the local fog server via a WIFI network. Sensor node has been built with a system on chips WIFI-Microcontroller ESP8266 to perform data acquisition and temperature sensor data transmission, relative humidity and light intensity using the WIFI network to the fog server. In this study testing the accuracy of sensor parameters used and network performance by comparing with the use of cloud networks. From the tests performed, the results of Mean Absolute Percent Error (MAPE) were obtained for each parameter, temperature = 1.3%, humidity: 1.9% and light intensity: 0.6%. The use of the fog network has proven to not contribute significantly to the error value of measurement data sent to the server. The use of WIFI on the fog network requires less network broadband needs when compared to cloud networks. This difference is very significant, which is an average of 253 BPS if using a fog network and 1276 BPS if using a cloud network. From the experiments conducted, the use of networks for proven to have a high data transmission speed with value 471 ms when compared to the internet network with value 1349 ms. Variations in the number of sensor nodes up to 5 nodes do not significantly affect that speed.
其他摘要：Greenhouse is a very effective method of matching and has been able to contribute to food independence in various countries. Plants that are in the greenhouse must be maintained with chemical-physical parameters in order to grow optimally. Monitoring of plants in greenhouses must always be done. Some monitoring reports have been made online so that they can provide solutions as quickly as possible if there is a disturbance on the plants. Unfortunately, online monitoring is still dependent on internet networks that require network infrastructure needs that have many limitations. As a result, many agricultural lands are not covered by the internet network to monitor the greenhouse. The use of a large number of sensor nodes also affects the decline in available broadband internet performance so as to reduce monitoring performance. In this research proposed a fog network that connects the sensor node with the local fog server via a WIFI network. Sensor node has been built with a system on chips WIFI-Microcontroller ESP8266 to perform data acquisition and temperature sensor data transmission, relative humidity and light intensity using the WIFI network to the fog server. In this study testing the accuracy of sensor parameters used and network performance by comparing with the use of cloud networks. From the tests performed, the results of Mean Absolute Percent Error (MAPE) were obtained for each parameter, temperature = 1.3%, humidity: 1.9% and light intensity: 0.6%. The use of the fog network has proven to not contribute significantly to the error value of measurement data sent to the server. The use of WIFI on the fog network requires less network broadband needs when compared to cloud networks. This difference is very significant, which is an average of 253 BPS if using a fog network and 1276 BPS if using a cloud network. From the experiments conducted, the use of networks for proven to have a high data transmission speed with value 471 ms when compared to the internet network with value 1349 ms. Variations in the number of sensor nodes up to 5 nodes do not significantly affect that speed.
