Terry is an autonomous home security system that utilises drone technology in conjunction with artificial intelligence to create the ultimate personal security guard for homeowners. The aim of Terry is to prevent potential burglaries by creating a presence in the home.



Terry works by connecting the homeowners alarm system, an autonomous drone and the Terry app to protect the home. Our concept works by using sound and audio to prevent potential burglaries by creating a presence in the home through an autonomous drone. The Terry app works in conjunction with the drone, allowing home owners to be informed the second a potential threat is detected, while also alerting and making neighbours aware of potential threats.

YEAR: 2018



Initially we started brainstorming autonomous technologies, systems and devices. We found that there were multiple types of autonomous devices for example drones, robots, IOT products and the Cohola Wireless. Autonomous vehicles included devices used for mining, collecting waste, farming and moving people (eg. Trains, planes, cars and boats). Autonomous systems which encompassed human interaction, navigation, banking, decisions and processes. After individually researching each of these autonomous technologies we decided that we were most interesting in autonomous devices specifically drones and robots. 

The next step was to start researching what type of problem areas we were interested in. We threw around various topic areas for example emergency services, health and banking however in the end we decided that we were interested with the idea of improving home security through the addition of artificial intelligence. We felt that there was huge potential in applying autonomous technology to home security as there aren't many products out there that incorporates autonomous technology with home security. We eventually decided on the scenario 'How can we reduce robberies and increase home security through autonomous technology?'.
The next step was to conduct user research to understand what the market demands and needs regarding the topic of home security, but also perspectives on innovative autonomous technologies. We decided to conduct the following methods:
Secondary Research: To understand the range of problems when encountering autonomous technology and home security. Also to explore the current technologies and options for users today.
Surveys/Questionnaires: To gage out the large audience and understand what users current feelings are regarding home security and autonomous technology.
Interviews: To get an in-depth and more personal understanding of how users feel about their home security and autonomous technology.
Affinity Diagram and User Journey Map: To synthesise information gained from users in the initial research stages.

Problems encountered while conducting our user research was that we realised that all our data was extremely similar as we had interviewed the same target audience of individuals aged from 18-21. After speaking to our tutor we then decided that we had an inadequate depth and amount of data that we could gain insights on so we decided to split up our research by researching various types of homes for example houses, share houses and apartments. This would mean that our data would be varied and we could gain more insights compared to if we conducted the same research methods on the same demographics. These insights have been integrated with our user research data from our first round of user testing.​​​​​​​​​​​​​​

With our context and scenario of home security in mind, we conducted background secondary research and found a range of interesting insights. While researching pre-existing autonomous devices for home security, we were able to get a better grasp on what is currently on the market and how we can build upon what already exists. These included the types of home security systems individuals today have, which include camera cctv systems, alarm systems, video intercom systems, access control systems and perimeter. Other insights gained included reasons for burglars to target a premise, successful deterrent and common methods of entry.
For our survey/questionnaire, we came up with a range of questions relating to either artificial intelligence and what current home security users have. From this we gained a range of findings:
-V45% of participants had sensor lights and gates/fences followed by 35% with camera and 25% with alarms.
- When home alone, 65-70% of people felt safe and relaxed compared to 14.3% feeling lonely, tired and anxious.
- When home with other people, 68-90% of people felt safe and relaxed, with 0% of people feeling scared, lonely and anxious.
- 68.2% of participants had been previously burgled, with robbers entering their home through open windows, fences and locked doors.
- Participants associated home security with security systems, a safe neighbourhood, dogs, cameras, sensors and secure locks on doors and windows.
- Participants thought artificial intelligence was interesting, good, scary, intimidating, frightening, complicated, unnecessary and futuristic.
- 45.5% of participants said they would feel safe if their home security was AI based, while 40.9% maybe and 13.6% said no.

For interviews, we interviewed around 15 people to get a broad range of data. So what key insights were gained?
- Visibility is fundamental for a good home security system as it creates an environment that deters criminals eg. visible CCTV camera
- In the current home security market, major concerns regarding home security surround a clash between old outdated products, and new innovation that consumers are unaware about.
- With the rise of smart technology, particularly that of facial recognition and smart security locks, AI would allow security cameras and security locks to work interconnectively, thereby creating a more severe environment that would not only aid in deterring crime, but may prevent it at whole.
- The nature of participants relationship with neighbours influenced their level of home security in either a negative or positive.
- Participants who lived in low income earning suburbs were more reckless with their home security compared to those with higher income earning suburbs.
- Alarms were the most popular type of home security followed by sensor lights and fences.
- Participants felt more un-safe at night compared to the day.
- Participants felt scared when home alone for reasons such as not being able to defend themselves, strange sounds and due to the fact that it is easier for burglars to rob houses at night.
- Participants who lived in apartments had more security for their home and thus felt safer
- When asked what type of homes participants felt was the safest most replied with apartments and houses.
- Most participants felt unsure about how the felt about AI, citing AI as ‘scary’, ‘not trustworthy’, and still ‘in the process of learning’ .
- Participants shared the feelings above regarding AI based home security, saying that their home security could easily ‘be hacked or fail’.

After combining our research and insights, we then decided to conduct synthesis methods to help us combine all our data. From our affinity diagrams, we were able to grasp that most homeowners thought:
Artificial intelligence was very risky and not trustworthy
Some thought it was interesting an innovative
Users thought that in general their home security could be improved, for example they would often forget to lock up their house or turn their alarms on.
Our journey map also allowed us to grasp a better understanding of the thoughts and feelings of users through their experience of home security.

As a team, we decided to focus on people living in houses as we saw more opportunities to create an effective autonomous device compared to an apartment or a share house. Following this, we also identified that there were several aspects/features that deterred robbers from entering home premises. These included:
- Loud alarms
- Lights
- Shapes eg. Human silhouettes and animals
- A presence in the home

We decided that these factors are all effective in deterring the robber as it scares as well as increases the risks the robbers take. As a result our design evolved into scaring the burglar. Our research into share homes found that a presence in the home makes the house less of a viable option for burglars. Thus our initial concepts were based around the idea of 'a presence in the home' in order to scare off burglars. In order to star coming up with initial ideas, we decided to conduct brainwriting in order to get us thinking quickly that would best suit our problem. Using this method we were able to come up with a range of different concepts and ideas regarding home security. These included:
- Drone(s) able to protect the home 24/7
- Alarm system that can be controlled by voice recognition
- Create an autonomous robot that monitors the perimeter of the house
- Face recognition sensor at the front door
- Similar to a “Roomba”. This takes care of the belongings in houses


The Autonomous Beehive Concept focuses on protecting the home through 24/7 surveillance of the surrounding home environment. The concepts envisions bee’s protecting the home by surveilling the home 24/7 and having the ability to autonomously detect if there is unidentified activity in their homes. The concept also has an app, which allows homeowners to view a live camera feed if there is unidentified activity and receive notifications/alerts.

This Autonomous Flower Concept also focuses on the idea of camouflage. The flower will also act as decoration within the house. A camera will be installed into the flower to monitor the inside of the house. When a burglar intrudes the home, the flower will shine a bright flash of light and take a photo of the burglar. The goal of this light is to scare the burglar. The flower will also trigger an alarm and notify the homeowner via mobile phone about a potential threat in the house.

An Autonomous Drone that firstly replicates the user’s presence in the house while they are away to make it look like the house is occupied, and secondly, to alarm the user if their house is being broken into whilst detering the threat with the use of alarms. The drone would patrol the house whilst playing audio such as dogs barking, conversation, or the sound of people doing everyday house tasks to replicate the feeling of someone being in the house. This no longer makes the house a viable option for intruders.

The Marble Drone Concept focuses on the idea of camouflage. This concept is quite futuristic as marbles do not have any propellers. A handful of marble drones will be kept inside a bowl and it will act as decoration in the house (in the image in page 14, the marble drones are placed on the coffee table). The drones will deploy from the bowl once the house is empty. The drones will fly around and monitor the inside of the house through the cameras implanted into them. If a burglar intrudes, the drones will sound an alarm and record the potential threat that is present in the home. The house lights are also connected to the drones and so when a burglar enters the home, all the lights in the house will immediately turn on to expose the burglar (this will be most effective at night).
We then pitched our initial concepts with our tutor however feedback received casted doubt on whether our ideas were realistic enough. We then decided to brainstorm new concepts again as we felt that our previous concepts weren't strong enough to take forward into the prototyping stage. These new concepts were:

Concept 1: Outdoors
- There will be a few drones monitoring the outside perimeter of the house
- The drone will have audio implemented into it in order to scare off/deter burglars
- If one of the drones detect any potential threats they will sound an alarm
- At night, if the drones detect a threat they will sound an alarm and also shine a light on them to expose the burglar
- It will be linked up to the home user’s phone in order to notify the user
- The drone will also have a camera installed into it
- The drone will automatically deploy and start monitoring the house when the house is empty

Concept 2: Indoors
- There will be a few drones stationed indoors (the amount of drones depends on how big the house is)
- The drones are small and so it will be harder for the burglar to detect
- The drones will have audio implemented into them in order to create a presence in the house (e.g. people talking and laughing sound effect). This will also increase the chance of a burglar avoiding the house
- They will be linked up to the home user’s phone in order to notify the user
- They will also trigger an alarm if an intruder breaks in
- The drones will also have a camera installed into them
- The drones will automatically deploy and start monitoring the house when the house is empty

After evaluating our two proposed concepts, we decided that we wanted to further iterate on concept 2, as we felt that it best suited our goal of 'a presence in the home' compared to concept 1 which we felt was impractical as we would face numerous problems for example 'what if it starts raining?'. We also decided that creating a drone that would be able to deter potential robbers through the implementation of audio and lighting whilst simultaneously monitoring the home was innovative in the methods if secured the home, but also in creating a presence in the home.


After deciding to go with concept 1, we decided to further iterate on our concept through the creation of two interfaces for our concept, our first interface would be an app while our second interface would be a smart speaking system. To assist us with the creation of our two interfaces, we decided to sketch out storyboards to help us envision our future concept and scenarios.

Below show two concepts for future use scenarios:
Scenario 1 envisions Terry as an app interface
Scenario 2 envisions Terry as a smart speaking system
Next, we decided to start doing low fidelity prototypes of our two interfaces through paper prototyping. Creating low fidelity paper prototypes allowed us to get a greater grasp on what our high fidelity prototype and final design would potentially look like.

However after we talked to our tutor we felt that our interfaces were quite lacking in terms of its features and the justification of why we decided to put in certain things and miss certain things. As a group we made the decision to redo our interface design and first started by mapping our all our features and justification of why we decided to include them. From there we created our two low fidelity paper prototypes again and felt happier with them as opposed to the paper prototypes created previously. We then took pictures of all our screens and added them to the mobile application 'Pop' so that we could test our low fidelity prototype.

The app’s main purpose is for it to be a platform of communication between the homeowner and the drone. The app will allow the homeowner to have instant connection with the drone at home so that they can receive live information on any activities that occur in the home. The drone will only deploy and start monitoring the house, once the homeowner has left the house and their phone is 50 metres away from the house. The app also gives the option for the homeowner to notify police of a potential threat in their home. Neighbours also have the option of installing the “Terry” App. If a house is getting burgled, the app will notify neighbours that there is a potential threat in their neighbourhood. The aim of this is to raise awareness for neighbours to be wary of their safety and be secure in the home (e.g. a neighbour receives a notification from the app and immediately acts by closing all the windows and doors in their home).

Check out the 'Pop' low fidelity paper prototype here: https://marvelapp.com/19cf3776

For our second interface, Terry is a smart speaking system (like Siri) that communicates with the user via talking. As a group we believed that simply speaking to Terry would be more natural and convenient for the user. This speaking system is also a platform of communication between the drone and homeowner. The drone will only deploy and start monitoring the house, once the homeowner has left the house and their phone is 50 metres away from the house. The smart speaking system will be integrated into any mobile device. Like the app, Terry will also give the option for the homeowner to notify police of a potential threat in their home. Neighbours will also be notified of any potential threats in their neighbourhood. Again, this is to raise awareness and safety in the area.

Check out the 'Pop' low fidelity paper prototype here: https://marvelapp.com/19djf5fg


In terms of user testing, we decided to conduct the following methods:
Contextual Observation: Contextual observation is a method in which the users testing the product are observed from a distance to minimize the amount of interference. This allows users to test the product freely, without any form of interruptions making the actions the user does free of influence from the testers (us).
Think Aloud Method: The think aloud method is a user testing method in which the users say their thoughts as they use the product. This allows testers to learn from what the user is thinking when they are using the product as well as their feelings and opinions. Instead of having the users think back and evaluate, the testers are given thoughts that have happened in the moments the user is using the product.
A/B Testing: A/B testing is a method where two different versions of the same product are tested by the user. The two products are then compared after both being tested by the user. This allows for testers to determine which product better suits the users need. After both products are tested by the user, the user must answer certain questions which will help the testers find out which product is more suitable.

We felt that user testing 3 people per team member would allow a greater depth of user data compared to if we decided to test less. Our user methods were also chosen as they would allow us to get a broad understanding of our users but most importantly the flaws and problems within our interfaces.

From there we then came together with all our user data and brainstormed all the problems that were discovered from both our interfaces. To synthesise our data, we evaluated our user feedback from our user testing via nielsons heuristics by establishing which heuristics we violated and solutions to how we can improve our interface. There were several inherent problems that we found, which were:

“House map was a bit confusing”
Many people found the house map confusing due to the fact it violates the heuristic of consistency and standards. As a group we came to the conclusion that the house map was not necessary and that the live feed was enough information for the user to see where the drone was located. As a result the house map was removed completely.
"Need a tutorial or walk through"
Users found that even though parts of the app were clear and easy to use they still required the use of a tutorial or help option. The lack of a tutorial violates the heuristics of error prevention and errors and recovery. As a result a tutorial was necessary and therefore implemented.
“There should be an option to sign out”
The heuristic of users sense of freedom and flexible/efficiency of use were violated due to the lack of the users ability to sign out. Giving the option to sign out has the potential to provide comfort in privacy as their phone may end up in the wrong hands causing other people to invade the homeowner’s privacy of their home. The sign out option also gives an opportunity for other people to log into their account on someone else’s phone in case of an emergency (the person lost their phone and is wanting to check their home security from a friend’s phone).  As a result the implementation of a sign out option was vital and later on implemented.
“What would happen if you had a pet?”
One of the problems posed were in relation to pets, which corresponds to Neilson’s Heuristic of matching the system to the real world. This was overcome with the implementation of the ability to add pets into the family system.

Following our user testing, we then evaluated which interface we felt was more user friendly and appropriate for our concept. After evaluating our feedback from the A/B Testing we established that the app had stronger reasonings in regards to the user’s preferences. Some of these included:
Pressing buttons provides more confirmation to the user
The speaking system may not be suitable for certain environments.

We also believed that we had more opportunities to effectively iterate on this concept rather than the Smart Speaking System. The user testing feedback also provided us with important insights into new elements that need to be included, aspects of the app that need changing, and removing elements that are not useful. Furthermore, after receiving a range of positive and negative feedback, we decided to implement these changes within our Mid Fidelity prototype. To create our mid fidelity prototype, we decided to use Sketch, as we felt it was the simplest and most effective way.

Check out our 'Pop' mid fidelity prototype here: https://marvelapp.com/a09cg21

Below is an in depth wireframe with annotations explaining the functionalities of the app and why it was implemented.
Following the creation of our mid-fidelity prototype, similarly to our low-fidelity prototype, we decided to test our prototype using the same guidelines (except for the A/B Testing). We received a range of mixed feedback that gave our group a lot to consider for the final prototype of our concept. From this, we discovered several things:

“Why is the sign out button in settings?”
Users questioned whether it was appropriate to put the sign out button in the settings. Suggestions included putting it in the home screen instead.
“I thought the Help/Search button was a Setting button”
Users were confused with the help/search button as some thought it was a settings button
“Adding an entry/exit entry would be convenient”
Users suggested adding an entry/exit history that allows homeowners to view family entering and exiting the home for safety.
“I dont understand how to add family and community members”
Users had trouble adding family and community members to their database however this was due to the fact that we had not iterating on the idea far.
“I want easier navigation”
Users wanted the navigation of the system to be easier, thus we thought that adding a home button to every screen on the header would be convenient.
“I want more features on the live feed”
Users wanted more features with the live feed as our interface only currently allows people to view it. Suggestions included being able to control the drone manually.
“Whats the plus button?”
Users struggled to understand the purpose of the plus button on the community and family screens.
“What if the phone and drone battery dies?”
Users brought up the unaddressed issue of what would happen if the smartphone and drone ran out of battery.
“I think it would be cool if i could speak through the drone”
Users suggested that the interface should have a feature that allows the home owners to speak to intruders through their smartphones.


After testing our concept, and analysing our feedback, we identified both the strengths and weaknesses of our current design. This has given our group a clearer vision of which strengths we should be pursuing, improving the overall design and quality of our interface. Some of the weaknesses that were highlighting through our user testing included the positioning of certain elements/features for example a sign out button or a add/plus button. Other complications that were discovered included what would happen when the drone or a smartphone ran out of battery. We also identified features of our interface that needed to be further iterated on which included how users would add community/family members to their databases. These user issues will be strongly considered and addressed while progressing onto the next stage of iteration which is creating a high fidelity prototype.
The following prototype is a High Fidelity Prototype of our application component from our concept 'Terry'. Feel free to click around! (This prototype was made using Invision)

Terry Main interface: https://invis.io/RJOOR50BN68
Terry Community notification interface: https://invis.io/6EOQ4FKWJKB
Terry Homeowner notification interface: https://invis.io/J4ORQNZ3A76

To create our high fidelity prototype, we decided to use Figma which allowed us to work on the prototype live collaboratively. While creating our high fidelity prototype, we strongly considered the feedback gained from our previous user testing and solved the problems that became apparent. After the completion of the creation of our high fidelity Terry app, we were generally happy with the overall outcome of our application. Above shows our functional and interactive high fidelity prototype, while below shows our walkthrough videos of our application Terry.


Prior to the user testing of our high fidelity prototype, we had decided that were were going to use the following methods:
Contextual Observation: Contextual observation is a method in which the users testing the product are observed from a distance to minimize the amount of interference. This allows users to test the product freely, without any form of interruptions making the actions the user does free of influence from the testers (us).
Think Aloud Method: The think aloud method is a user testing method in which the users say their thoughts as they use the product. This allows testers to learn from what the user is thinking when they are using the product as well as their feelings and opinions. Instead of having the users think back and evaluate, the testers are given thoughts that have happened in the moments the user is using the product.
For this batch of user testing, we decided to test three users.


From our user testing, we received some positive and negative feedback that provided us with great insight on our strengths and weaknesses. Some of the feedback we received were:
Users wished for more confirmation in the sign up/sign in screens
Users liked the simplicity of the layout
Users enjoyed being able to see the status of their community/neighbours
Users enjoyed the addition of the QR, however they were unsure of how to use it.
The layout of the home screen was simple and easy to understand
However overall users enjoyed the flow and navigation of the app
The next step was to analyse our feedback and make the appropriate changes which will be explored in our 'Recommendations'.


The final step of our process was to evaluate the feedback that we received from our user testing and make suitable changes for our final prototype. After considering the range of feedback we received from users, we decided to implement the following changes:
In general, create more confirmation screens for our processes eg. Our sign up/sign in screens
Create an option where users could enlarge their QR code to make it easier when they scan.
Thus, we decided to create our 'Final Prototype' following the feedback we received from our user testing.

The following videos will show a walkthrough of our application Terry.

Terry Main Interface
Terry Police Notification Interface
Terry Neighbour Notification Interface
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