This project is an attempt to understand, analyse and recreate the results and observation obtained from a research paper "Anomaly Detection in Molecular Communications
With Applications to Health Monitoring Networks". Additonally, we have tried to improve the results and add new observational analysis to paper.
Early detection of diseases such as cancer plays a
crucial role in their successful treatment. Motivated by this,
anomaly detection in molecular nano-networks is studied. The typical network for anomaly detection in a practical bio-molecular set-up comprises a two-tier
network architecture design. We detect the presence of the anomaly in the first tier using a nano
network within the body and we report the aforementioned anomaly to the larger scale network on the
outside in the second tier.
we have made an attempt to further the design problem from the previous set up to determine the optimum
threshold for the highest possible probability of detection and probability of false alarm. By devising
the probability of error, which relies on the aforementioned probabilities, we can observe the pattern
and attempt to find the least possible value.