TOMMY Roadmap

Discover what is coming next in TOMMY development. The roadmap is driven by community feedback and technical feasibility.

2025 Roadmap

November 2025

Home Assistant Integration

Native integration that automatically exposes motion zones as entities without requiring Matter setup.

Support for Using Sensors in Multiple Zones

Enable a single sensor to contribute to multiple adjacent zones, reducing the total number of sensors needed. For example, in an open-plan kitchen-living room, a sensor placed between the two spaces can detect motion in both zones, eliminating the need for separate sensors in each room while maintaining full coverage.

December 2025

Docker Installation Support for Mac and Windows

Expand Docker compatibility beyond Linux to support macOS and Windows hosts, making TOMMY accessible to more users regardless of their operating system.

2026 Roadmap

Q1 2026

Filtering Non-Human Movements

Distinguish between human motion and other movement sources like pets, fans, robot vacuum cleaners, and environmental factors.

Stationary Presence Detection

Detect when someone is present in a zone even when they're not moving, supporting room occupancy detection for sleeping, reading, or other stationary activities.

Q2 2026

Passive Devices as Sensors

Allow devices that are not flashed with TOMMY firmware to be used as passive sensors (e.g., Smart TVs, computers, gaming consoles). This feature will reduce the number of dedicated sensors needed.

Future Features (Timeline TBD)

The following features are planned for future development but do not have confirmed timelines as they depend on ongoing research and potential hardware improvements.

Activity Recognition

Identify specific activities being performed, such as:

  • Walking patterns and direction
  • Gestures like clapping or waving
  • Sitting, standing, or lying down
  • Exercise or movement routines

Human Identification

Identify specific individuals present in the environment, supporting personalized automations such as "set lights to scene ID when person X enters the room" or "play person Y's preferred music when they arrive."

Room-Level Localization

Detect approximate location of people within a space, supporting room-level positioning and automation based on where people are located within zones.

Fall Detection

Detect when a person falls within the monitored environment, supporting safety monitoring for elderly care applications, emergency response automation, and health and wellness monitoring without requiring wearable devices.

Development Priorities

Our roadmap is shaped by:

  • Community Feedback - Features most requested by users
  • Technical Feasibility - Current hardware and software capabilities
  • Research Progress - Advances in Wi-Fi sensing algorithms
  • Hardware Evolution - New devices and capabilities

This roadmap is subject to change based on technical discoveries, community feedback, and development priorities. Timeline estimates are goals, not guarantees.

Want to influence the roadmap? Join the discussion on Discord