Abstract

In a real life two places in same city have a different temperature like Garden and parks have a lower temperature comparatively to areas of buildings, streets,offices , industries etc .Basically in same city area can have have a different temperature based on its environ mental conditions and various human activities like urbanization . Due these differences in tempera-ture variation , the problem arises where local sensors aren’t useful to state the live temperature of different places precisely which causes Urban Heat Island Effect (UHI) like Tokyo in Japan ,London Heatwaves , Mumbai,Delhi in India has a majoraly affected by these . To resolve Ur-ban Heat Island Effect (UHI) Distributed Internet of Things (IoT) sensors can help to observe the live temperatures changes at local places.Along with those IOT integration we have LoRa mesh networking and solar energy harvesting as a tech nical approaches to become practical monitoring of temperature reliable communication, available energy, maintenance needs, and energy-efficient operations.This paper describes a Python-based simulation study of three con-figurations for urban heat monitoring : I)a solar-powered mesh network II) a mesh network without solar energy harvesting III) a solar-powered direct-communication network. These configurations are compared at different sensor-node counts using the perfor mance metrics produced by the performing simulation . The results are based on the as sumptions used in the model for implementation and are not real-world readings or data from physical sensors, a deployed LoRa network, or on field implementation.

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