Performance Analysis of IoT-based Temperature Monitoring Box Type Solar Cooker: A Multi-objective Optimization Approach
Authors: Swarnkar Harshita , Pandey R.K. , Prakash Vodnala Veda , Nayak Sasmita , Vasnani Himanshu , Jain Ritu , Tiwari Amit 
Published: December 2024

Background:
The idea behind the Internet of Things is to bring the virtual world into the
physical one by connecting commonplace items. With the help of the Internet of Things (IoT), it is
possible to remotely sense or control objects through preexisting network infrastructure. This opens
up possibilities for computer-based systems to integrate with the physical world, which in turn improves
efficiency, accuracy, and economic benefit while reducing the need for human intervention.

Objective:
The purpose of this patent study is to investigate how a (NSGA-II) multi-objective genetic
algorithm might be utilized to optimize the execution of an Internet of Things (IoT) temperature
monitoring Box-Type Solar Cooker (BTSC). To determine the best set of output parameters for
an IoT temperature monitoring box-type solar cooker, (NSGA-II) multi-objective genetic algorithms
are used to perform optimizations of the figure of merits (F2), cooking power, cooker efficiency,
and final water temperature.

Methods:
The present research work involves the development of a Wi-Fi module system integrated
with a smart temperature monitoring system for a BTSC. Keeping track of the temperature data
from different locations in the BTSC through the IoT system was the primary objective of this project.
A waterproof temperature sensor (DS18B20) was used to keep monitoring. After that, the data
was shown on an LCD, stored on a microSD card, and made available through a smartphone. The
Blynk Applications' IoT was employed. Using existing data, regression-based computational models
are developed to describe the complex correlations between the decision-processing parameters
and the input parameters of an IOT-based solar cooker. These models are applied in the objective
functions after determining that a genetic algorithm is more appropriate for the problem. To forecast
the optimal values about the figure of merits (F2), cooking power, cooker efficiency, and final water
temperature, the Pareto fronts have been developed.

Results:
We compare the values of response variables that were gathered experimentally with the
values that were predicted by NSGA-II. The predicted values are found to be quite close to experimental
values. This indicates that the multi-objective optimization method, as used in this study, has
very good prediction performance. The test results are graphically shown using the error bar. Therefore,
it is clear that the optimization process used to adjust the parameters of the solar cooker's performance
has been quite effective. According to the findings of the experiment, the temperature at
which a cooking pot remained stagnant on average was 158°C. It was determined that the cooker
was of class A based on the values of the first figure of merit (F1), the second figure of merit (F2),
and the cooking power (P), which were respectively 0.132, 0.359, and 86.108 W. Therefore, the
thermal efficiency of the IoT-base temperature monitoring box type solar cooker is 39.99 %.

Conclusion:
The findings of this inquiry furthermore produced the outcome that the model provided
can be applied conveniently with a confidence level of 95% to calculate the figure of merits (F2),
cooking power, cooker efficiency, and final water temperature value of an Internet of Things-based
temperature monitoring BTSC. The performance of IoT-based BTSC is optimized by providing real-
time monitoring and data visualization, ultimately improving their efficiency and reliability. This
research provides an educational tool to promote awareness and understanding of renewable energy
sources and their potential benefits.