Aurora Funzjoni Primarja: App Mobbli minn Ping Chen

Id-disinn Aurora Funzjoni Primarja: App Mobbli minn Ping Chen huwa rebbieħ stmat ħafna tal-prestiġjuż 2026 Premju A' Design Award tal-Ħadid fil-Kategorija tal-Kompetizzjoni ta' Disinn tat-Teknoloġiji Mobbli, Applikazzjonijiet u Software.

ĦadidMobbli· 2026

Aurora Funzjoni Primarja: App Mobbli

minn Ping Chen

Klijent: Aurora

Rebbieħ tal-Premju A' Design Award tal-Ħadid fil-Kategorija ta' Mobbli

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Rebbieħ ta' Premju Ivverifikat

Ivverifika l-Istatus tal-Premju għal #182515

Ara fuq A' Design Award Stqarrija għall-Istampa Badge tal-Premju

Kuluri

Id-Disinn

Dwar Aurora Funzjoni Primarja: App Mobbli

Test tal-Ktieb: Aurora hija app mobbli li tappoġġja r-regolazzjoni emozzjonali għal persuni bl-Adhd permezz ta' interazzjoni bbażata fuq il-mużika. L-interfaċċja tikkombina ġenerazzjoni ta' playlists imqabbla mal-istat, ġurnal b'diversi burdati, u sommarji ta' xejriet ta' kuljum. Kull entrata fil-ġurnal torbot il-biċċa mużikali kurrenti ma' sliders tal-intensità tal-burdata u nota qasira. Il-vista tax-xejriet tenfasizza l-mumenti ewlenin meta l-mużika tejbet il-konċentrazzjoni jew naqqset l-istress. Modalità viżwali sinkronizzata mar-ritmu tipprovdi sinjali ta' moviment ġentili waqt is-smigħ biex tappoġġja l-istabbiltà.

Ir-Rikonoxximent

Dwar il-Premju A' Design Award tal-Ħadid

Aurora Funzjoni Primarja: App Mobbli huwa rebbieħ tal-Premju A' Design Award tal-Ħadid, rikonoxximent prestiġjuż mogħti lil disinji tajbin li jissodisfaw ir-rekwiżiti professjonali u industrijali mistennija minn ħolqien imfassal tajjeb. Ir-rebbieħa tal-Ħadid juru l-ħila kbira, l-ispeċjalizzazzjoni għolja, il-fehim espert u l-kapaċità kreattiva tal-ħallieqa tagħhom. Huwa mistenni li Aurora Funzjoni Primarja: App Mobbli ikun ħolqien imqabbar ħafna, mammirat u maħbub li huwa prattiku u innovattiv. Dan id-disinn rebbieħ tal-Ħadid jintegra l-aħjar prattiki tal-industrija u għandu karatteristiċi tekniċi kompetenti marbuta mal-għarfien u t-talent. Aurora Funzjoni Primarja: App Mobbli huwa rispettat għall-eżattezza tiegħu u mfassal biex itejjeb il-kwalità tal-ħajja u jgħin jagħmel id-dinja post aħjar.

Wara d-Disinn

Kit għall-Istampa

Krediti, membri tat-tim u dettalji tekniċi pprovduti mid-disinjatur.

Proprjetajiet Uniċi: Aurora is a music-based emotional support app for people with ADHD. Unlike traditional music platforms that recommend by genre or history, Aurora learns from users' mood journals to generate state-matched playlists, highlight moments when music helped, and reveal daily regulation patterns. Rhythm-synced visuals add gentle grounding during listening. The result is a low-effort tool that turns everyday songs into long-term self-regulation habits for wellbeing support.
Dimensjonijiet u Ippakkjar: Platform: Mobile app (iOS and Android concept). Core inputs: current track metadata, time stamp, multi-mood intensity sliders, and short text notes. Core outputs: state-matched playlists, daily mood pattern summaries, highlighted key moments, and rhythm-synced visual modes. Data model links each journal entry to a song and a time period to support calendar navigation and trend views. Visual modes include multiple selectable patterns designed for low stimulation.
Tikketti: ADHD support, emotional regulation, mood based playlists, music journaling, rhythm synced visuals, neurodiverse wellness, focus support, calm support, behavior design
Teknoloġija tal-Produzzjoni: Aurora is designed as a mobile app concept with interactive prototypes. The experience is structured around three modules: playlist generation, mood journaling, and visual listening mode. Mood inputs are captured with multi-dimensional sliders and saved as time-stamped entries linked to the current music track. The app then summarizes entries into daily patterns and generates state-matched playlists based on past mood and listening records. Rhythm-synced visuals are designed to respond to BPM and audio energy.
Sfida tad-Disinn: The main challenge was designing for mixed emotional states without adding cognitive load. Many mood trackers force a single label, while detailed journaling can feel too demanding for ADHD users. This was addressed by using a small set of mood dimensions with quick sliders, blended visual cues to reflect mixed states, and an insight-first trend view that highlights only the most meaningful moments instead of showing every entry.
Riċerka: Research Objectives: Understand how people with ADHD use music to manage focus and mood.
Methodology: Semi structured interviews and concept testing. Data Collection and Research Tools Used: Interview notes, affinity mapping, storyboard and UI prototypes.
Participants: 10 adults with ADHD. Results: Music helps regulation but playlists rarely match the moment and helpful tracks are hard to recall.
Insights and Impacts: Led to mood logging, pattern highlights, and state matched playlists. Effect of the Research in Real-Life Phenomena such as Business, Society and Design Itself: Supports neurodiverse wellbeing and reframes music as intentional support.
Ispirazzjoni: After interviewing 10 people with ADHD, I saw a repeated pattern: music helps them focus or calm down, but generic playlists rarely match the moment, and it is hard to remember what worked later. This gap inspired Aurora. I combined mood journaling, pattern insights, and rhythm-synced visuals to turn listening into a repeatable self-regulation tool.
Tul tal-Proġett: Aurora was designed over approximately 8 weeks in the United States (Boston, MA). Work included user interviews, synthesis, concept development, wireframing, and high-fidelity UI prototyping.
Fluss tal-Operazzjoni: Users listen to music, then log a quick moment: what they are listening to, how they feel across a few mood sliders, and a short note. Aurora turns these moments into state matched playlists and a daily trend view that highlights when music helped stabilize focus or calm. A visual mode adds gentle rhythm synced motion during listening to support grounding and reduce overstimulation.
Privattivi: Copyrights belong to Ping Chen, 2025.
Membri tat-Tim: Ping Chen
Haowei Zang