Darkness Driven Retail Automation

This project focuses on automating the response of a retail environment to changing light conditions and customer density, aiming to reduce energy costs and increase advertisement effectiveness. The inspiration comes from Asimov's 'Nightfall', where society panics when darkness falls (triggering a lighting response), and 'Interstellar', where resource management in changing environments is key. The 'Retail Sales' scraper project provides the customer density data.

Story/Concept: Imagine a store that dynamically adjusts its lighting and advertisement displays based on the amount of natural light and customer presence. When the sun sets or clouds roll in (like the onset of night in 'Nightfall'), the store automatically brightens its interior lights. Simultaneously, brighter, more visually appealing advertisements are displayed on digital screens to attract customers passing by in the dimming light. If the customer traffic is high (sourced from a real-time retail sales scraper monitoring transactions or camera-based people counting integrated with an API), advertisements for specific products with higher turnover or sales targets are prioritized (inspired by Interstellar's resource prioritization). During low traffic periods, the lighting dims and advertisements switch to promoting less popular, but high-margin items, or providing more general brand awareness messages.

How it works:

1. Ambient Light Sensor: An inexpensive light sensor (e.g., a simple photodiode connected to a microcontroller) continuously monitors ambient light levels inside and outside the store.
2. Customer Density Data: A scraper continuously monitors a retail sales database (or API of a camera based people counter) to estimate real-time customer traffic within the store or entering the location. The scraper extracts transaction data or customer count data to determine current customer density.
3. Microcontroller/Single-Board Computer (e.g., Raspberry Pi): This device receives data from the light sensor and the scraper. It acts as the central processing unit for the automation.
4. Relay Control Module: The microcontroller controls a relay module that switches the store's lighting system on and off (or adjusts dimming levels using PWM signals) based on the light sensor readings.
5. Digital Signage Display Control: The microcontroller also controls the content displayed on digital signage screens. Based on both light levels and customer traffic, it selects appropriate advertisement content from a predefined library (e.g., images or videos promoting specific products or general branding). This could involve simple selection based on predefined thresholds, or more advanced machine learning models if budget allows.

Implementation:

- Low-Cost: The components (light sensor, microcontroller, relay module, repurposed display screen) are relatively inexpensive. Scraping can be initially done manually, then automated with readily available libraries.
- Niche: Focus on smaller retail environments (e.g., boutique stores, local supermarkets) where personalized, data-driven solutions are valuable.
- Earning Potential: By reducing energy consumption and increasing sales through targeted advertisements, this system can generate significant cost savings and revenue increases for the retailer. The service can be sold as a subscription, offering varying levels of customization and support. Additional revenue can be generated via advertisement sales withing the system.