ChronoSustain Bot

Inspired by the foresight and predictive elements of '12 Monkeys' and the idea of creating something unique from scattered parts like 'Frankenstein,' this project focuses on a niche in the booming sustainability market. 'Customer Behavior' scraper forms the technical backbone. The concept is to build a lightweight, automated bot that monitors specific online forums, subreddits, and social media groups dedicated to sustainable living, ethical fashion, zero-waste products, or eco-friendly tech. It would scrape discussions, product mentions, sentiment analysis around new product launches, and importantly, identify trends related to products nearing discontinuation or becoming scarce due to ethical sourcing challenges or limited production runs.

Story/Concept: Imagine a 'time traveler' for sustainability. Our bot, the ChronoSustain Bot, acts as a digital oracle. Instead of preventing a plague, it aims to ensure individuals don't miss out on crucial sustainable products that might disappear from the market. It's about building a resilient, personalized supply chain for the eco-conscious consumer. The 'Frankenstein' element comes in as we're assembling disparate pieces of online information into a functional, predictive system. The '12 Monkeys' inspiration lies in the proactive, almost prescient nature of identifying future scarcity and acting upon it.

How it Works:
1. Niche Identification: The user defines their areas of interest within sustainability (e.g., specific brands of biodegradable cleaning supplies, ethically sourced coffee beans, upcycled furniture components).
2. Scraping Module: A Python-based scraper (using libraries like `BeautifulSoup` and `Scrapy`) targets predefined online communities and product pages. It focuses on keywords related to 'discontinued,' 'last batch,' 'limited edition,' 'ethically sourced,' 'backordered,' and product-specific discussion threads.
3. Sentiment & Trend Analysis: Basic Natural Language Processing (NLP) techniques would be applied to gauge community sentiment towards specific products and identify emerging trends or concerns that might lead to scarcity.
4. Prediction Engine: A simple rule-based system or a more advanced machine learning model (if the user has the inclination and data) would flag products showing signs of future unavailability or high demand in niche circles.
5. Automated Alert & Procurement: Upon prediction, the bot triggers an alert to the user via email or a notification service (like Pushbullet). Optionally, it can be configured to automatically add items to a user's wishlist on specific e-commerce platforms or even initiate a pre-order if supported. For low-cost implementation, it can focus on alerts and wishlisting, leaving the final purchase to the user.

Implementation: This is highly feasible for individuals. The scraping part can be done with readily available Python libraries. The NLP can start with simple keyword matching and expand. Hosting can be done on a low-cost cloud server or even a Raspberry Pi. The niche focus on sustainable products and scarcity significantly reduces the competition and targets a growing, high-value market. Earning potential comes from enabling users to secure sought-after sustainable goods, saving them money by avoiding inflated secondary market prices, and potentially partnering with sustainable brands for early access or affiliate marketing through the platform.