PRAMAN

Praan is a deep-tech startup democratizing access to clean air through innovative purification technology. Their hardware, the HIVE for commercial spaces and MK II for industrial facilities, needed a digital companion that could make air quality data meaningful and device management effortless. Pramaan is the IoT-enabled mobile application I designed to connect users with their Praan purifiers. It provides real-time air quality monitoring, device health tracking, spatial scanning for optimal placement, and an educational layer that helps users understand the science behind what they're breathing.

I was the sole designer on this project, working on it as a design assignment for the company. My responsibilities included: • End-to-end UX design: from research and information architecture to hi-fi screens • Defining the interaction model for IoT device management • Designing data visualization for air quality metrics • Creating a spatial scanning flow for purifier placement • Building an educational content framework • Establishing a minimal, trust-forward visual language

Commercial spaces face significant challenges in managing indoor air quality. The core issues: • Limited awareness: most facility managers don't understand AQI readings or what constitutes dangerous pollutant levels • Inadequate understanding of pollutants: PM2.5, PM10, and their health implications are invisible to most people • Ineffective use of purification systems: purifiers are often poorly placed, poorly maintained, and running without any feedback loop • No connection between data and action: even when air quality data exists, users don't know what to do with it There was a clear need for a solution that doesn't just display numbers, but translates complex environmental data into actionable insights and makes managing purification hardware intuitive.

I defined three core objectives that formed the design's "linear stack": 1. Increase public awareness: help users understand why air quality matters and what the real health risks are 2. Make the science simple: translate AQI data, particulate matter readings, and pollutant types into language anyone can understand 3. Make the product accessible: ensure device setup, monitoring, and maintenance require zero technical expertise

The app is structured around four core modules, each accessible from a bottom navigation bar: • Air Quality: real-time AQI index, PM2.5/PM10 readings, historical data, ideal levels, and actionable tips • Device Info: status, filter health, positioning, and maintenance for each connected purifier (MK One, MK One 2, IoT Device) • Scan Space: AR-based room scanning to guide optimal purifier placement • Learning: educational content covering health effects, measurement methods, environmental impact, and AQI improvement tips Each module was designed to stand alone while connecting back to a unified home dashboard that surfaces the most critical information at a glance.

I started with low-fidelity wireframes to map out the core flows before committing to visual design. This helped validate the information hierarchy and navigation model early. Key decisions made at this stage: • Home screen as a dashboard hub with quick-access cards for each module • Progressive disclosure: surface summary data first, let users drill into details • Consistent card-based layout across all sections for scannability

The visual language was guided by four principles: Simple, Soft, Contrast, and Balance. I chose a predominantly monochrome palette with selective color use: yellow for highlighting active data points and status indicators, and color gradients only for the AQI scale where color-coding is essential for quick comprehension. The minimal aesthetic reinforces trust and keeps the focus on the data that matters.

The home screen acts as a command center, surfacing the most critical data from each module in a single view: • Current AQI level with severity label (Good/Moderate/Poor) • Device status with connected hardware count • Scan space accuracy percentage for placement optimization • Learning module entry point Each card is tappable, leading to its full module. The design prioritizes glanceability: a facility manager checking in during their day should get the full picture in under 3 seconds.

The air quality screen translates raw sensor data into understandable information: • AQI index displayed prominently with a color-coded severity scale • PM2.5 and PM10 readings broken out individually with their own status indicators • Location-aware data (Pune, MH, IND) with temperature and humidity context • Historical forecast data showing AQI, PM2.5, and PM10 trends over time The color gradient bar (Good → Bad) gives instant visual feedback without requiring users to memorize number thresholds.

The device info section gives users full visibility into their connected purifiers: • Each device card shows status (ON/OFF), position, filter health percentage, and last check date • Expand view reveals a detailed technical illustration of the purifier with component-level health indicators • "Needs Attention" alerts use a pulsing red indicator to draw focus to maintenance needs I used line-art illustrations of the hardware to help users identify physical components without needing technical documentation.

Drilling into a specific device reveals granular status information: • Component-level health visualization with the actual purifier anatomy • Red pulse indicator on specific components that need attention • Status, position, filter percentage, and health rating at a glance This diagnostic view helps facility managers understand not just that something needs attention, but exactly where the issue is on the physical device.

The scan space feature uses the phone's camera to help users find optimal purifier placement: • Phone-guided room scanning with real-time feedback • Placement accuracy scoring to indicate how well-positioned a purifier is • Position guides based on room geometry and airflow patterns This feature directly addresses the problem of ineffective purifier placement, one of the key reasons commercial spaces don't get full value from their air purification investment.

The learning section closes the awareness gap by educating users on air quality fundamentals: • Health effects of poor air quality • Measurement methods and what the numbers mean • Environmental impact context Each topic includes video content, charts, and the option to save for later. The design keeps educational content approachable rather than clinical, making it more likely that busy facility managers will actually engage with it.

The complete screen set showing the app's visual system in context, from the isometric component explorations to the full hi-fidelity flows across all four modules.

Looking back, there are a few areas I'd push further: • User testing with actual facility managers: the design was informed by research but not validated with real users in commercial environments • Notification and alert system: the current design focuses on active monitoring, but passive alerts for AQI spikes or filter degradation would make the app more proactive • Multi-site management: commercial operators often manage multiple buildings, and the current IA is designed for a single location