This week I mainly worked on the final presentation and doing end-to-end testing. I worked with Surafel in completing speed and distance tests to ensure that only users within 0.5 meters of the camera would be recognized and that they would be recognized within 5 seconds. This involved doing various tests by changing our distances from the camera and fine tuning the facial recognition algorithm with any results were unexpected. For testing the entire system, I asked several volunteers to check in and check out items on the rack and ensured that the rack successfully displayed their items upon checkout. Lastly, I prepared for the final presentation since I would be the speaker. I spent some time practicing delivering the presentation, ensuring I was well informed about all components of our project and that the design trade-offs and testing procedures were clearly explained.
My progress is on schedule as I have completed all the parts of the project initially assigned to me, including unit and integration testing.
Next week, I hope to work with the other members of the team to wrap up the project. I will mainly work on completing the facial recognition and the web application. If there is time, I will also work on implementing the bonus feature, the buzzer alert, along with various tests to ensure this feature works as intended with the rest of the system.
These past 2 weeks, I mainly focused on doing testing. This involved testing the integrity of the item stand, determine if our system met our timing requirements, and doing end-to-end testing with the entire system (including the item stand and facial recognition). For testing the integrity of the item stand, I wanted to ensure that the stand could withstand a large amount of weight placed on it. Each hook should be able to hold up to 20 pounds and the Nema 34 motor should be able to rotate the maximum weight of 120 pounds that we expect. In addition to this, I tested if our system could quickly recognize users, and rotate to a specific user’s position within 5 second. I worked with my team on fixing the motor speed and acceleration as well as looking more into the blocking behavior of our wireless transmission. We ensured that the speed at which the motor rotated would be safe for users and we ensured that the entire check-in and check-out process occurred relatively quickly. I also helped with testing the facial recognition with my team members, helping to develop new approaches and implementations to improve the accuracy closer to our target of 95%. Other than testing, I worked on adding code to determine if an attacker attempted to steal user belongings from the item stand. This involved introducing a buzzer and writing code to make it alert user if anything was removed from the stand while not in a check-out process. The implementation of the buzzer does not work yet, but in further weeks, I hope to further test it.
My progress is slightly behind. This week, after introducing the buzzed to our system, our system unfortunately broke. As a result, we had to spend time to determine which component led to the failure. With my team members, we determined that the wireless transceiver were not working, so we had to get new ones. The additional time to debug this issue and receive new parts delayed out end-to-end testing, causing us to have less time to tune our algorithms. I plan to do more testing next week to prepare for the final demo, ensuring that our facial recognition system can accurately detect new faces and that our item stand can correctly find good positions for users to place their items.
I plan to spend some time next week to further test the system and try to satisfy any design requirements that were not met. This involves doing more end-to-end testing, and improving the speed at which users can complete the check-in and check-out processes. I also plan to re-introduce the buzzer code so that we can detect if attackers have stolen items on the stand.
As I’ve debugged the project, I found it necessary to learn more about facial recognition. I have had to look into the differences between SVM versus euclidean distance classifiers, and I’ve learned about ways to normalize faces. In terms of hardware, I’ve had the opportunity to learn about how to calibrate load cells and do wireless transmission to communicate between two Arduinos. I also have written more code in Arduino, so I improved my skills in this aspect. In terms of debugging, I have learned to do unit testing on individual components to locate which parts of the system led to failure. I have also relied on online tutorial and forums to learn about new approaches to solving problems dealing with both hardware and software components of our system, like load cells, motor, and facial recognition.
This week, I mainly worked on preparing for the interim demo. This involved doing some end-to-end testing with the hardware components and the facial recognition system. There were issues relating to wireless transmission between the Python code for the facial recognition and the Arduino code, so I worked with my team members to fix those issues. We realized that the readline function that we utilized would block on many trials, so we had to deduce where to problem was and how to fix it. We thought about various solutions like flushing input and output buffers, but ultimately realized we had to add some delays in various locations of our programs to ensure that the subsystems were in sync. In addition on this integration, I tested the Nema 34 motor and helped write code to control the motor upon an check-in or check-out process. This involved spending time in the TechSpark wood shop to carve a hole in the rack to place the motor and mounting the motor sturdily to the rack using brackets and nails. Additionally, I worked on code to control the motor, allowing it to rotate to a user’s position on the rack.
My progress is slightly behind schedule. I have worked on testing various components of our system, including the load cells, motors, and wireless transmission. However, the complete system has not been tested together thoroughly, with members outside of our group. In addition, the LEDs which indicate to the user whether they have successfully placed their items on the rack has not been permanently installed, so a bit more time in the wood shop is required to do that. In order to catch up, I will need to add the LED and do further testing using volunteers to ensure that the system works as a whole.
Next week, I will work on adding the LEDs to the rack. I will also work on doing end-to-end testing. Further details are provided above.
Although we notice that our system works mostly as intended, I would like to further optimize delays for the check-in and check-out process. The delays added for transmitting information make it so that our timing requirements (taking less than 5 seconds for a using to be recognizes) are not meant. As a result, I would like to find the smallest delays that allows message transmission without blocking behavior. Secondly, I would like to test if each hook on the rack can withstand the maximum weight ( 20-25 pounds) previously set in our use case requirements. This will involve place 20 pound backpacks on our rack and seeing if the motor can successfully rotate that much weight. In a similar regard, I would like to ensure that even with weight imbalances, the motor can successfully rotate the items on the rack. I will do this by placing a large weight (20 pounds) on one side and nothing on the other. I will also check-in 6 times to fill the entire rack, then remove all items on one side, to ensure that the motor successfully rotates the weight and that the thread on the gears are not impacted.
This week, I mainly worked on writing code to transmit data between 2 Arduinos. This involved using 2 wireless transceivers to test whether commands could be sent back and forth between them. I worked on this with Ryan. Together, we tested whether a command could be sent from one Arduino to the other to control an LED. Once this worked, we tested if we could send commands to control the motors connected to the Arduino on the coat rack. After creating the data structures and specifying the communication between the two sides, I helped in testing the integrating between the facial recognition system and the components on the rack, with Ryan and Surafel. This involved transmitting data from our python program and being able to rotate our motors when someone attempted to check-in and check-out. We have found some issues when testing this, and plan to continue our integration efforts and fix any software problems that arise upon further testing.
My progress is slightly behind. Although a majority of the work for the hardware components and associated code has be finalized, our team still plans on making further changes, like replacing our current motors. According to the scheduling, we are solely supposed to be integrating the different components of our systems, but with this change, we need to work on integration while we make the necessary motor changes to ensure that we can satisfy our use case requirements. In addition to this, with integration, there is a possibility that we may realize that system components that seemed to work on their own, may not work together, which may require additional work to fix.
For next week, I will continue working on integrating the facial recognition system with the hardware system. Although we have been able to successfully transmit data from our python program to the Arduino Mega on the rack using wireless transceiver, I want to ensure that users can successfully check-in and check-out. In addition to this, I want to ensure that the motor can correctly turn to the position specified by a user’s item position on the stand. In addition to working on these software aspects for the project, I want to complete the hardware aspect by substituting the Nema 17 motor with the Nema 34 motor, which is expected to arrive next week. I would like to test that the holding torque for the motor actually satisfies our use case requirement, sustaining rotation with up to 20 lbs on each of the 6 hooks on the rack.
This week, I continued working on the hardware portion of the project, as well as started writing the programs to control the hardware components. These tasks were accomplished as a team with my teammate, Ryan. I first ordered inserts for the load cells, so that we would be able to attach them to the stand using M4 bolts. This involved drilling in the inserts, placing the load cell above them, the attaching the bolts. Now the top of the stand contains the load cells and hooks. In regards to the load cells, we calibrated them so that they would display weights in pounds. Additionally, I helped with testing our motor, successfully being able to control the speed and position of the NEMA 17 motor. We attached the motor to the stand, and have started testing whether our use case requirements, specifically the weight requirement of 25 lbs on each hook, would be achievable. Upon further testing, we realized that our first motor driver did work, and have since begun using it to control the motor as it has a higher maximum current rating. Our entire team tested wireless transmission between two Arduino boards, and were successfully able to communicate between them.
My schedule is currently on track with the Gantt chart we created in previous weeks. According to the Gantt chart, I should be assembling the rack with the electronic components. I have tested individual components, and am now ready to write the programs which will control the hardware components.
Next week, I will continue working on ensuring that the rack can withstand the required weight as described by our use case requirements. This will involve adding a second motor to the stand, as only one motor, was not powerful enough. In addition to this, I will write code for transmitting data between the web application and stand. This code will define what data is transmitted when a user attempts to check-in or check-out an item. Overall, the upcoming week will be dedicated integrating between different system components and further testing.
This week I worked with my team member on the hardware component of the project. This involved painting the rack and creating cutouts for electronic components. We determined the placement of the load cells, slip ring, and power cord on the rack. To ensure that these components could be placed, we had to make more cutouts on the stand. In addition to this, we assembled the bottom portion of the stand by attaching L brackets to the base and legs of the stands. Furthermore, I helped with testing the load cells. Although we had tested them in previous weeks, we wanted to see if the power, ground, and clocks line could be combined for the load cells, which required further wiring and testing.
According to our Gantt Chart, we are still on schedule because we anticipated the current setbacks. Our schedule states that we should be assembling our rack and adding the electronic components, which is what we are currently working on. However, we need to ensure that we have less setbacks with the motor, by quickly testing our new motor driver, in case we need to make additional plans to ensure that we can accomplish our requirements.
For next week, I will help test our motor driver controller and wireless transceiver. In addition to this, I will help further assemble the rack, so that it is at a more completed state. Refer to the team status report for updated media/images.
This week, I continued working on the coat rack portion of our project. This involved finishing cutting and sanding our plywood pieces in the woodshop in TechSpark, as well as adding nails to some pieces to ensure the multiples layers of wood would remain together. I also worked with my teammate in staining some of the pieces and designing a gear that would rotate the rack. Lastly, I contributed to our design report by writing several portions and adding corrections were needed.
My progress is currently on schedule. However, since the rack is not fully assembled and we do not have the parts to power our motor, we are not able to test if the rotation will work. As a result, we need to quickly order parts and complete assembly next week so that we can test rotation.
Next week, I hope to complete an order for more materials so that we can have all necessary materials to power/use our electronics. I hope to continue workin on the coat rack, finishing painting it and also test the rotation. Lastly, I hope calibrate the load cell so we can begin adding various weights on the rack.
This week, I worked on building the rack. This involved drawing the shapes for the frame on 1/2 inch plywood and cutting them out in the wood shop in Techspark. Since many pieces needed to be cut, and I did not have training to use the machines in the wood-shop, the only tools that were used were jigsaws and drills, making the process longer than initially thought.
My progress is only schedule according to the timeline. However, with multiple midterms in the upcoming week, it will be difficult to carve out time to finish building the rack. I hope to completely focus of this after my exams on Wednesday if I do not find time in the beginning of the week.
For next week, I hope to finish building the rack with my team member, so that we can begin adding the electronic components. I also hope to carve out time to learn how to use Coreldraw to design the gears that we will need to rotate the rack. I also plan on helping to write the design report.
This week, I research the possible facial algorithm tools that we were considering for our project (OpenCV and dlib). I focused my research on the feasibility of using the tools, and analyze the differences between them. I found that OpenCV has extensive documentation and it easy to use. Howeverm it has limited facial recognition capabilities in comparison to dlib. On the other hand, dlib’s facial recognition module offers advanced capabilities but the learning curve is high. Since our team’s use case does not require advanced facial recognition capabilities and none of the members have done facial recognition in the past, we decided to use OpenCV for our purposes.
I worked on the design presentation slides with my team members and helped with thinking about design changes to the rotating rack system. I also spoke with peers and employees at the Techspark wood shop to start planning which machines we could use and if any tools existed for assembling the rack. I obtained a name of a person we could connect with to help build our rack, so next week I plan to reach out if any challenges arise while we begin building the rack.
I ordered the materials that we would need to make our rack.
I am currently on schedule, but plan to learn more about how to utilize OpenCV.
Next week, I plan to help build the rotating rack system and test the electronic components that were ordered.
This week, I contributed to project proposal slides by making Gantt chart and developing use case requirements. I helped my team member prepare for the proposal presentation and attended project proposal presentations. I also researched facial recognition tools like OpenCV and dlib.
My progress is on schedule, according to our Gantt chart.
Next week, I plan to work with my team members to finalize which facial recognition libraries we will utilize. I also plan to determine the feasibility of building current rack design by asking Techspark employees. This involves seeing if they would be able be cut the wood used for our rack component if we are not able to use the machines ourselves. I also plan on working on the design presentation and begin assembling the rack if the components arrive.
