Changes between Version 57 and Version 58 of Other/Summer/2023/Hive

Timestamp:

Aug 1, 2023, 4:31:37 PM (16 months ago)

Author:

Sonimal05

Comment:

—

Other/Summer/2023/Hive

@@ -21 +21 @@
 
 == **Progress**\\
+
 == **Week 1**\\
 **Project Goal**: The project's objective is to assess electromagnetic radio frequency (RF) impact on bees, particularly bee mortality, inspired by the lead epidemic's significance. It aims to examine how human-emitted RF affects bee populations and ecosystems. 
 
-**Apparatus Mockup**: Designed a system with an apparatus connected to a bee hive. Glass tubes would be connected to a system of pipes, to see the bee motion. 
+**Apparatus Mockup**: 
 
-**Machine Learning Analysis**: We will use artificial neural networks to classify videos using the pytorch libraries. The results will produce the accuracy of the bees detecting the magnetic field. 
+**Machine Learning Analysis**:
 
 == **Week 2**\\
 **Experiment Design**:
 
-**Apparatus Construction**: Modeled and figured out the correct sizing of the base wood, built and cut the camera mount, cleaned and fixed the glass tubes on the coil. 
+**Apparatus Construction**: Modeled and figured out the correct sizing of it. The correct dimensions were found in order to cut and build the base. The glass tubes were cleaned and fixed. Lastly, a camera mount was established.
 
-**Raspberry Pi**: Studied the raspberry pi pinout and wrote code on the raspberry pi to control different states of the magnetic field. 
+**Raspberry Pi**: ILAB was starting to get set up as well as running the machine learning scripts. Raspberry Pi Pinout was studied and code was written on it to control different states of the magnetic field. 
 
 == **Week 3**\\
+**Camera Setup**:
 
-**Data Collection**: Collected videos of the bees using raspberry pi and used machine learning to analyze the videos. 
+**Data Collection**: Videos of the bees were collected using the Raspberry Pi. The motion of the bees was observed depending on the different magnetic states. Machine learning would be used to analyze these videos.
 
-**Eliminating Extraneous Sources**: Constructed the black box around the data collection area of the tube
-
+**Eliminating Extraneous Sources**:
 
 == **Week 4**\\
@@ -52 +53 @@
 **Camera Calibration**: The CV camera calibration library was opened. The camera needed to stop being distorted while being at a wide field view.
 
-**
+**Machine Learning**: The neural network was being trained to detect behavioral responses from the bees and the magnetic field. PyTorch libraries were utilized to run the machine learning scripts. Accuracy indicates how well the neural network classified the videos. 
 
 == **Week 6**\\