This final thesis project is a set of tools controlled by a companion business to business (B2B) mobile app, designed for traveling musicians, providing stress free gig tech. The data from the sensors in the ami modules enable the physical smart gig companion tags and tools in the ámi system to use the onboard machine learning (ML) chip and provide up-to date feedback to the touring musician.The realtime data update provides access to the status of the gig gear. The artificial intelligence (AI) hypothesis on the data collected solves some critical concerns uncovered during research with musicians and gig rental companies. The decision support hypothesis and analytics is shown on the companion mobile app. The system is non intrusive, the design is a natural part of the ecosystem, with limited or no change to the existing equipment.
PERSONA
RESEARCH INTERVIEWEES
EXPERIENCE MAP
STAKEHOLDER MAP
CMF AND MOODBOARD
EARLY STAGE PROTOTYPES
CMF AND MOODBOARD
AMI PHOENIX
Smart, connected, handheld scanner with accompanying smart tag. Real-time inventory mapping and asset auditing system.
On-device confirmation of assets as per packaging list. Scans individual to a whole array ami tagged gear. Live analytics decision making report.
AMI HAQUE
A biometric, thermal, multi sensor security system built into the gig gear handles allowing user-device mapping for security and authentication.
Geo fencing range for better location security and insurance needs.
AMI MAYA
Instrument and gear health monitoring system. Includes GPS, humidity, pressure, impact, and gyro sensors.
Stores on-device ML data for predictive AI tasks.
COMPANION APP
FUTURE CONCEPT: NEXT STEPS
AMI BANDWAGN
A customizable gig van, mobile rehearsal space, lounge where the musician(s) can rest, rehearse, record, broadcast, write songs and have their personal space.
