WiFi Signal Strength Degradation Over Different Building Materials

Wireless Fidelity (WiFi) signals experience propagation through air and material in a building. This propagation causes signal decreasing signal strength. This study aims to determine materials in buildings that cause significant signal strength loss so in the future building design could factor in signal strength by using material that doesn't affect signal strength significantly. The testing of signal strength will be done by observing signal strength through different materials. Signal strength will be recorded by using a mobile app. Materials that majorly decrease signal strength are plastics, with the least affecting materials are hollow plywood wall. The use of plastics in a building affects significantly on signal loss and should be replaced if possible with hollow plywood walls.

Convolutional neural network based evil twin attack detection in WiFi networks

Evil Twin Attack (ETA) refers to attackers use a device to impersonate a legitimate hotspot. To address the problem of ETAs in the WiFi network, a Convolutional Neural Network (CNN) attack detection method is proposed. The method uses the preamble of the WiFi signal as the feature and uses it to train a CNN based classification model. Next, it uses the trained model to detect the potential ETA device by the inconsistent of the identity it claims and the signal feature. Experiments based on the commercial hardware demonstrate that the proposed method can effectively detect the Evil Twin Attack.

INTERNET OF THINGS: AUTOMATIC PLANT WATERING SYSTEM USING ANDROID

Internet of Things (IoT) is a system that connects devices directly or indirectly to the internet. The device can work with remote control. One application of the IoT system on the watering system is able to provide an approach to the ease in the process of growth and development of plants. The research carried out was applied to an IoT-based smart plant watering device. The tool is supported with a soil moisture measuring sensor that acts as a benchmark to determine the condition of soil moisture and automatic control of the process of watering plants. The process of watering plants is scheduled in the morning and evening. Information, as long as the device is run will be displayed on the LCD and screen of an Android-based smartphone application. The data can be a comparison value to determine the suitability of soil moisture data in plants. The volume of water supplied in the watering process also affects the level of soil moisture. IoT-based smart plant sprinklers can automate watering by measuring the percentage of soil moisture as a benchmark for providing water during the watering process. Remote watering control can also be done on this tool by using a WiFi signal to the same access point that is connected to the smartphone client and microcontroller. Keyword: agriculture, automatic sprinklers, engineering, IoT