For my pervasive design course, I was tasked with conducting user research to help solve a problem that involves an interactive physical prototype. The solution was a physical PAWLS device + PAWLS mobile application. Throughout the semester, multiple user research design methodologies were used, including a Competitive Analysis, Contextual Inquiry, Surveys, Diary Studies, User Enactments, Wireframing, Hardware & Software Prototyping, Usability Testing, and a Concept Video.
PAWLS is a smart crate system that decreases disruptive barking in dogs with positive reinforcement and stimulus masking methods. It can collect and analyze data around your dog’s barking, what triggered the barking, and provide personalized recommendations for users detailing steps that the owner can take to aid the training. There are two components to PAWLs, the physical crate that uses pervasive technology and the mobile application that gives users the power to access all the collected data in digestible form and it also allows them to control the crate.
PAWLS could be called a comprehensive training solution that guides new dog owners through the training process and facilitates the development of healthy behaviors and a strong bond between owner and companion. Based on our findings, we believe this system will address the needs of dog owners whose companions are experiencing behavioral issues.
Each year, approximately 6.5 million companion animals enter shelters in the US. Less than half of these animals are adopted. One of the main reason why animals are returned is behavioral issues. In order to address this issue of pet homelessness, we decided to explore how ubiquitous computing can do two things: decrease the number of dogs being given up by their previous owners to shelters and ensure that adopted dogs stay adopted and remain in their new homes.
For our survey, we wanted to understand how we could define our scope and concepts by focusing on what specific behavioral issues dog owners are dealing with, and how common they occur.
For our diary study, we wanted to understand how dog owners addressed behavioral issues right as they’re occurring, along with the context surrounding those issues. For a week, participants kept a behavioral log for every time their dog experienced any emotional distress. The first part of the diary study allowed us to better understand each dog’s unique history and temperament.In the second part of the diary study, participants were tasked with keeping a behavioral log of every instance of their dog experiencing any distress, when and where it occurred, what triggered the dog’s response, how serious the dog’s response was, and what the owner’s did about the dog’s distress.
Once the diaries were returned, each entry in the behavioral log was carefully analyzed, including each specific trigger, location, the dog’s response, and how the owner responded to the dog’s inappropriate behavior. An Affinity wall was generated in Trello, where a thematic analysis was done to help discover any common themes between the participants and their dogs.
Our experience prototyping study involved conducting five user enactments with each of our five participants for a total of 25 user enactments to answer our four research questions. Through the user enactments, we wanted to understand users’ perception and the strengths and weaknesses of our product in varying scenarios.
While earlier research informed us about user’s general pain points, it was in this stage of our research that we were able to directly observe users interacting with our product in the way they would in their home. As a result, we were able to observe the user's authentic reaction to our suggested features, rather than just abstract ideas. It was these reactions that helped us gain a more accurate understanding of if and how our ideas were addressing user needs and the pain points we had previously identified.
PAWL's camera system and accompanying app lets owners check in with their dogs from anywhere and even talk to their dogs using the speakers. Using sound sensors, PAWLS can even detect when the dog is barking and attempt to mitigate the negative behavior. With treat dispenser, the owner can give treats to the dog anytime with just one click from the app. PAWLS app even integrates with smart blinds and the crate door to help alleviate any stimulation that may be distressing your dog.
The PAWLs smart kennel is constantly sensing your dog’s emotional levels using sensors to help recognize and react to various triggers that may occur when the dog’s owner isn’t home. Using that data, PAWLs will aid the dog owner in properly training the dog so it will be less distressed when the owner is not home. A mobile app that communicates with a web-based database & IoT cloud platform would have to be set up to properly connect a PAWLs user to the device when they aren’t home. Due to the sensitive nature of placing microphones and cameras in an owners home, it’s important to create a privacy policy that clearly states how the data will be used and protected with the use of encryption.
After researching various IoT microcontrollers, I decided on utilizing a Raspberry Pi 3 Model B+ instead of an Arduino or Particle Board. The Raspberry Pi’s quad-core processor is best suited for processing and streaming the high-definition video PAWLs required. The Raspberry Pi’s extensive DIY community helped guide our software implementation, which involved running open-source “Motion” software, which offers extensive options related to recording video streams. We also needed to identify a camera that could record the entire area within a kennel using a fish-eye style lens.
Materials included:
PAWLS focuses on helping new owners by providing an assistant that senses when the dog is agitated, scared, or in need of their owners. PAWLS is essentially a smart crate system that attempts to decrease disruptive barking in dogs. It has the capability to collect data about a dog’s barking, its potential triggers, and suggests actions that the owner can take to help their dog. There are two components to Pawls, the physical crate that uses pervasive technology and the mobile app which gives users the power to access all the collected data in digestible form and control the crate.
Each year, approximately 6.5 million companion animals enter shelters in the US. Less than half of these animals, however, are adopted. In order to address the rampant issue of pet homelessness, we decided to explore how ubiquitous computing can do two things: decrease the number of dogs being given up by their previous owners to shelters and ensure that newly adopted dogs stay adopted and remain in their new homes.