LSTM Enabled Artificial Intelligent Smart Gardening System
| Autor: | Dongkyun Kim, Malik Muhammad Saad, Muhammad Toaha Raza Khan, Muhammad Ashar Tariq |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Artificial neural network
business.industry Computer science 0211 other engineering and technologies Mac layer protocol 02 engineering and technology Term (time) Wide area network Default gateway 0202 electrical engineering electronic engineering information engineering Bandwidth (computing) 020201 artificial intelligence & image processing business Internet of Things Protocol (object-oriented programming) 021101 geological & geomatics engineering Computer network |
| Zdroj: | RACS |
| DOI: | 10.1145/3400286.3418260 |
| Popis: | In the present era, internet of things (IoT) is prevailing very much in our daily life serving the concept of the smart applications, in which one can operate remote objects from a distant place. However, connectivity of the billions of devices has become a major concern in most of the prevailing researches. Massive connected devices used for smart applications consumes the network resources such as bandwidth and consumes the power to operate. Due to limited bandwidth, intermittent connectivity issues arises between smart devices which incorporates delay in the network. LoRaWAN (Long range Low power wide area network) developed by SemtechTM is a MAC layer protocol developed primarily for the IoT devices. In this paper, we implemented Long Short Term (LSTM) based smart gardening system, where end nodes collect the data from surrounding and sends to gateway using LoRa protocol. Edge Server is installed with the gateway on which LSTM based machine learning algorithm is running which predicts the future sensor values. For the predicted interval of time gateway sends the message to end nodes to remain inactive which saves the network bandwidth and also increases the life of sensors. |
| Databáze: | OpenAIRE |
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