Overview
Fixlark explores home maintenance journal through a mobile experience built around an appliance passport with document tabs and photo history. A home-records app for appliance-label capture, document retrieval and service-appointment preparation. The proposed journey connects appliance passport, label capture, ask my records, home timeline. Four original phone showcases establish the visual direction, while the case study defines the supporting feature set and a proposed Java architecture.



Original mobile interface concepts with fictional content. AI responses illustrate proposed interactions; they are not live model results.
Challenge
Householders need model details, manuals and service notes together without relying on generated repair directions. On a phone, the person also needs to capture information quickly, understand where an answer came from and return to the original material without navigating through a dense desktop interface.
- Keep appliance passport and label capture connected within a short mobile flow.
- Make model-label extraction correctable when the model misreads the input.
- Explain appointment preparation through visible references or user-selected preferences.
- Keep changes, sharing and data retention under explicit user control.
Solution
The design begins with an appliance passport with document tabs and photo history, using large touch targets, short task sequences and contextual sheets. Draft appliance identifiers with uncertain characters highlighted. Locate relevant manual pages and saved service records. The companion views keep drafts, original material and accepted decisions distinct. A navy, warm gray and lime visual system gives this app its own character within the collection.
- Draft appliance identifiers with uncertain characters highlighted.
- Locate relevant manual pages and saved service records.
- Summarize user-entered issues into an editable service brief.
- Suggest document categories for the owner to confirm.
Results
4
Original mobile
showcase views12
Designed
feature areas4
Proposed AI
workflows


