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Visually impaired has the limitation in interacting with another human. They usually use the sense of hearing and touching their face to recognize human. Face recognition is a technology that can be used to solve this problem. This paper develops a smart cane function by integrated face recognition feature on the cane using Haar-Like features and Eigenfaces. This paper proposed a portable, real time, and wearable product. Raspberry Pi supports portability that affects the delay and computing speed of face recognition algorithms. Utilization of Raspi camera on the eyes glasses is for wearable purposes. Voice output provides information on whether the face is caught on camera or not. This prototype works well during the face detection and recognition process. It needs 3 seconds for one-face recognized in range 0.25 until 1.5 meters from the camera, until the sound and information are generated. It needs is me 5 second for two faces recognized and 10 seconds for 3 faces recognized by a system in the same range between face and the camera. The accuracy reaches 91.67% for the upright position face but for other position the accuracy is only 18% until 32%.

Nowadays, monitoring of guppy fish farming is still done manually. A monitoring and control system is needed to make it easier for guppy fish farmers. This system consists of a sensor module and monitoring module. Sensor module detects the value of pH and salinity of water and send it to the monitoring module. Monitoring is used as a web-based system using IoT technology. This web-based system serves to monitor and control the pH value and only monitor the salinity value. The workings of the monitoring and control system send data on pH and salinity sent by the sensor and then stored and in database hosting. Data on the database will be displayed on the website using wireless media, making it easier for users to view data and information remotely. Beside, farmers are facilitated in knowing the value of pH and salt content dissolved in water. For the value of a dangerous salt content worth less than 160 and more than 210, if for a pH of less than 6.5 and more than 7.5. Farmers are also facilitated to control pH with servo motors through the website, so farmers can prevent if the pH content dissolved in water is dangerous for guppy fish.

Monitoring irrigation is still the problem of agriculture in Indonesia. During the dry season, the farming fields drought while in the rainy season, floods happened. Since the farm-fields located far from the urban area, it requires an automatic tool for monitoring the availability of water that can help the farmer to monitor the farm-field. Wireless sensor network is an appropriate technology used to overcome problems related to the monitoring system. This research is using a water level sensor, pump, Arduino Nano, and XBee Pro S2C in each monitoring node. The system designed within two modules, an automation irrigation module and a monitoring module, which is connected with the communication configuration of master-slaves between Xbee Pro S2C at each node. The system examined several scenarios in order to test the performance. Based on the testing result, all the performance parameters can be adequately delivered to the user and appropriated with the real condition in the farm field. The delay between nodes only takes 5-10 seconds.

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