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An Energy-Efficient Hybrid LoRa-Wi-Fi Architecture for Real- Time Water Quality Monitoring and Machine Learning-Based Trend Forecasting.

energy-efficient hybrid lora-wi-fi architecture real- time is a B.Tech project topic for Environmental Engineering. Explore the IEEE-style abstract,…

energy-efficient hybrid lora-wi-fi architecture real- time is a B.Tech project topic for Environmental Engineering. It gives students a clear starting point for research, implementation planning, and documentation.

energy-efficient hybrid lora-wi-fi architecture real- time Project Details

Abstract

This framework guides the design and build of an energy‑saving hybrid LoRa‑Wi‑Fi network for real‑time water‑quality monitoring and prediction. Typical water‑quality stations use a lot of power and can only send data a short distance. To fix that, the proposed system uses two wireless links. Low‑power LoRa radios collect data from sensors placed in the water and send it to a nearby gateway. The gateway then uses Wi‑Fi to push the data quickly to the cloud. The sensor package measures the most important water parameters: pH, turbidity, temperature, and electrical conductivity. On the software side, machine‑learning models run in the application layer to forecast future water‑quality indices from past trends.

The document helps researchers fine‑tune duty‑cycling algorithms for the sensor nodes, set up the hybrid LoRa‑Wi‑Fi protocols, and test regression or time‑series forecasting models. By pairing long‑range LoRa telemetry with high‑speed Wi‑Fi, the system balances a long device life with reliable data transmission.

Reference Paper An Energy-Efficient Hybrid LoRa-Wi-Fi Architecture for Real- Time Water Quality Monitoring and Machine Learning-Based Trend Forecasting.
Domain Environmental Engineering
Sub-Domain Water Quality Monitoring
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