# BAN Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/ban
> Markdown URL: https://aitinkerers.org/technologies/ban.md
> Technology record last updated: 2026-04-23T13:59:49Z
> Generated: 2026-09-20T16:36:17Z

IEEE 802.15.6 defines the high-reliability standard for short-range wireless communication inside or around the human body.

Body Area Network (BAN) technology utilizes low-power nodes (sensors and actuators) to facilitate medical monitoring and consumer electronics. Operating primarily in the 2.4 GHz ISM band or via Medical Body Area Network (MBAN) spectrum (2360-2400 MHz), it supports data rates up to 10 Mbps. Systems like the Medtronic Micra pacemaker or Dexcom G6 glucose monitors leverage these protocols to transmit physiological data to external hubs with minimal latency. The standard prioritizes extreme energy efficiency (extending battery life to years) and stringent security to protect sensitive biometric packets.

- Official technology site: https://www.ieee802.org/15/pub/TG6.html
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Visual prompting for fun and profit](https://portland.aitinkerers.org/talks/rsvp_fGAlJQAvWUA)

Cloud hosted LLMs (such as GPT4 by OpenAI) charge per-token. Depending on the length of your input, this can become expensive, if not impossible. When building RealEstatePulse, I came across the challenge of needing to extract structured data from city zoning codes that were hundreds of pages long -- well passed the capabilities of even the largest LLMs. Moreover, there was a heavy dependence on textual layout (for example, with tables). The extra HTML markup blew up the token count and made analyzing zoning codes very expensive. However, recent research in LLMs have shown that the world model they acquire from textual learning translates well into visual question answering. Moreover, there is good reason to believe that current models are highly redundant, meaning they can theoretically process a lot more data than what the token embedding layer produces. Some cloud LLMs, such as GPT4, offer the option of visual input. Unlike text input, visual input is charged at a flat fee depending on the size of the image. I would like to present the technique I developed for analyzing extremely large zoning codes by rendering the text as an image and using this to prompt GPT. I will show that this makes the problem tractable and produces good results.

- Event context: AI Tinkerers Portland Inaugural Meetup - July — 2024-07-24 — Portland
- Public talk page: https://portland.aitinkerers.org/talks/rsvp_fGAlJQAvWUA

## Related Technologies

- [CLIP](https://aitinkerers.org/technologies/clip) ([Markdown](https://aitinkerers.org/technologies/clip.md)) — 10 public demos
- [GPT-4](https://aitinkerers.org/technologies/gpt-4) ([Markdown](https://aitinkerers.org/technologies/gpt-4.md)) — 529 public demos
- [HTML](https://aitinkerers.org/technologies/html) ([Markdown](https://aitinkerers.org/technologies/html.md)) — 9 public demos
- [LXMERT](https://aitinkerers.org/technologies/lxmert) ([Markdown](https://aitinkerers.org/technologies/lxmert.md)) — 4 public demos
- [MCAN](https://aitinkerers.org/technologies/mcan) ([Markdown](https://aitinkerers.org/technologies/mcan.md)) — 1 public demo
- [Multimodal LLMs](https://aitinkerers.org/technologies/multimodal-llms) ([Markdown](https://aitinkerers.org/technologies/multimodal-llms.md)) — 1 public demo
- [OpenAI](https://aitinkerers.org/technologies/openai) ([Markdown](https://aitinkerers.org/technologies/openai.md)) — 112 public demos
- [PyTorch](https://aitinkerers.org/technologies/pytorch) ([Markdown](https://aitinkerers.org/technologies/pytorch.md)) — 273 public demos
- [TensorFlow](https://aitinkerers.org/technologies/tensorflow) ([Markdown](https://aitinkerers.org/technologies/tensorflow.md)) — 90 public demos
- [Transformers](https://aitinkerers.org/technologies/transformers) ([Markdown](https://aitinkerers.org/technologies/transformers.md)) — 148 public demos
- [ViLBERT](https://aitinkerers.org/technologies/vilbert) ([Markdown](https://aitinkerers.org/technologies/vilbert.md)) — 4 public demos