A.Inspiration Cities are getting hotter every year, and urban heat islands are becoming a serious challenge. Roads, concrete buildings and rooftops absorb and retain heat, while the lack of trees and green spaces makes many urban areas increasingly uncomfortable. We noticed that most existing monitoring solutions focus on measuring temperature and displaying readings. However, simply knowing that a particular area is hot does not solve the problem. What if we could also understand why it is hot, explore possible solutions and identify which intervention would be most effective? This idea inspired us to create EcoSoothe – an intelligent platform that goes beyond monitoring and helps transform environmental data into actionable climate solutions. Our vision is to make urban climate intelligence affordable, accessible and useful for smarter city planning.

B.What it does EcoSoothe is an IoT-powered urban heat intelligence platform that detects localized heat hotspots, analyzes environmental conditions and recommends suitable cooling interventions. Our solution focuses on four major capabilities: Heat Detection: Uses environmental sensors to measure ambient temperature, humidity and surface temperature. Heat Analysis: Compares different surfaces and identifies unusual temperature variations to locate potential heat hotspots. Climate What-if Simulator:Allows users to explore possible interventions such as planting trees, installing cool roofs and creating shaded spaces, and compare their estimated cooling impacts. Carbon Intelligence: Estimates potential cooling-related electricity savings and associated CO₂ emission reductions using transparent assumptions. The most innovative part of EcoSoothe is its Climate What-if Engine. Instead of simply reporting that an area is hot, it helps users understand what could be changed and which cooling solution may offer the greatest benefit.

C.How we built it We designed EcoSoothe as a combination of affordable IoT hardware, a web-based dashboard and a climate intelligence engine. For the hardware, we selected an ESP32 microcontroller, an MLX90614 infrared temperature sensor and a DHT22 temperature and humidity sensor. The ESP32 collects environmental readings and communicates them to the dashboard through Wi-Fi. On the software side, we use Arduino IDE and embedded C++ for sensor integration and firmware development. The dashboard is designed using HTML, CSS and JavaScript to display sensor readings, temperature comparisons and visual analytics. We developed the intelligence logic around three main functions:

A heat anomaly detection system that compares measured surface temperatures with ambient conditions.
A rule-based recommendation engine that suggests potential cooling interventions based on the detected conditions.
A Climate What-if Simulator that compares intervention scenarios based on estimated cooling benefits, implementation costs and potential carbon savings.

D.Challenges we ran into Sensor accuracy: Getting consistent surface temperature readings requires maintaining suitable sensor distance, angle and measurement conditions. Hardware integration: Connecting multiple sensors to the ESP32 and ensuring reliable data communication required careful testing. Meaningful data interpretation: Raw temperature readings alone are not sufficient to identify urban heat problems, so we needed to develop a meaningful comparison and scoring approach. Climate simulation: Estimating the impact of interventions such as tree plantation and cool roofs is complex because actual results depend on several environmental factors. Time and budget constraints: We had to prioritize the most important features while keeping the prototype within our available resources. We addressed these challenges by focusing on a modular architecture, explainable decision-making logic and scenario-based calculations rather than making unsupported claims about predictive accuracy.

E.Accomplishments that we're proud of What makes us proud of EcoSoothe is the idea of turning a simple environmental monitoring device into a platform for climate decision-making. Some of the key accomplishments of our project include: 1.Designing an affordable IoT-based approach to localized urban heat monitoring. 2.Combining ambient and infrared surface temperature measurements. 3.Developing a concept for identifying heat anomalies across different urban surfaces. 4.Designing an interactive Climate What-if Engine to compare possible cooling interventions. 5.Integrating carbon intelligence to estimate potential energy savings and associated emission reductions. 6.Creating a scalable architecture that can eventually support multiple sensor nodes across campuses, residential communities and cities.

F.What we learned Through EcoSoothe, we learn that building a meaningful ClimateTech solution requires more than collecting sensor data. Environmental measurements must be interpreted carefully and connected to decisions that can create real-world impact.