1
Department of Computer Science & Engineering, University Institute of Technology, Rajiv Gandhi Proudyogiki Vishwavidyalaya (Technological University of Madhya Pradesh), Bhopal, Madhya Pradesh, India
(piyush@rgtu.net)
Abstract :
There is annual financial loss, mental pain, bodily injury, and loss of life due to natural and artificial disasters. Unfortunately, natural disasters are becoming much deadlier due to climate change. Consequently, IoT-based catastrophe detection and response systems have been developed to improve the handling of catastrophic disasters and other times of extreme urgency. As a consequence, information gathered from Internet-connected devices is utilized to aid in the categorization of several types of disasters, both natural and artificial. A determination of the nature of the crisis and notification of the relevant command center is accomplished using preexisting methods. We have shown how to modify an existing system into a particular early warning system for natural disasters using two Internet of Things (IoT) devices: the Arduino Uno and the Nodemcu. Using this data, we can pinpoint the exact position of every person whose phone is within range of the disaster and send them warnings before the situation worsens. The botmasters have shifted their paradigm away from IRC and toward an HTTP-based C&C server due to the widespread use of HTTP services. Like HTTP bots, IRC bots have a single point of failure. HTTP bots, however, are harder to stop. It is also challenging to detect HTTP botnets while keeping the false positive rate low since every service on the Internet utilizes the HTTP protocol. This chapter provides a host-based HTTP botnet detection approach that uses Hidden semi-Markov Model (HsMM) variables and the Simple Network Management Protocol-Management Information Base (SNMP-MIB). The device operates following the specifications established by the LoRa network. In this project, we used a device called Nodemcu, which was made to be configured explicitly on the receiving end to identify the users at the place where the catastrophe was detected. At that point, everyone connected to the gadget would receive a geolocation-based alert. MQTT is used to notify the right people when an issue arises. We saw better and more beneficial results from the IoT project after including LoRa.
Keywords :
LoRA; MQTT; Internet of Things; Arduino Uno and Nodemcu; Machine Learning
References :
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| Style | # |
|---|---|
| MLA | Piyush Kumar Shukla. "Natural Disaster Detection for Smart IoT Communication using LoRA model." International Journal of Wireless and Ad Hoc Communication, Vol. 6, No. 1, 2023 ,PP. 19-29 (Doi : https://doi.org/10.54216/IJWAC.060102) |
| APA | Piyush Kumar Shukla. (2023). Natural Disaster Detection for Smart IoT Communication using LoRA model. Journal of International Journal of Wireless and Ad Hoc Communication, 6 ( 1 ), 19-29 (Doi : https://doi.org/10.54216/IJWAC.060102) |
| Chicago | Piyush Kumar Shukla. "Natural Disaster Detection for Smart IoT Communication using LoRA model." Journal of International Journal of Wireless and Ad Hoc Communication, 6 no. 1 (2023): 19-29 (Doi : https://doi.org/10.54216/IJWAC.060102) |
| Harvard | Piyush Kumar Shukla. (2023). Natural Disaster Detection for Smart IoT Communication using LoRA model. Journal of International Journal of Wireless and Ad Hoc Communication, 6 ( 1 ), 19-29 (Doi : https://doi.org/10.54216/IJWAC.060102) |
| Vancouver | Piyush Kumar Shukla. Natural Disaster Detection for Smart IoT Communication using LoRA model. Journal of International Journal of Wireless and Ad Hoc Communication, (2023); 6 ( 1 ): 19-29 (Doi : https://doi.org/10.54216/IJWAC.060102) |
| IEEE | Piyush Kumar Shukla, Natural Disaster Detection for Smart IoT Communication using LoRA model, Journal of International Journal of Wireless and Ad Hoc Communication, Vol. 6 , No. 1 , (2023) : 19-29 (Doi : https://doi.org/10.54216/IJWAC.060102) |