|1||CHARM: CHeap Accessible Resilient Mesh for Remote Locations and Disaster Relief
|# CHARM: CHeap Accessible Resilient Mesh for Remote Locations and Disaster Relief
- Martin Michalski (martinm6)
- Trevor Wong (txwong2)
- Melissa Pai (mepai2)
There are many situations in which it is difficult to access communicative networks. In disaster areas, internet connectivity is critical for communication and organization of rescue efforts. In remote areas, a single internet connection point often does not cover an area large enough to be of practical use for institutions such as schools and large businesses.
To solve these problems, we would like to create a set of meshing, cheap, lightweight, and self-contained wireless access points, deployable via drone. After being placed by drone or administrator, these access points form a WiFi network, usable by rescuers, survivors, and civilians. Our network will have QoS features to prioritize network traffic originating from rescuers. Having nodes/access points deployable by drone ensures we are able to establish timely connectivity in areas where search and rescue operations are still unable to reach.
Over the course of the semester, we will produce a couple of prototypes of these network nodes, with built in power management and environmental sensing. We aim to demonstrate our limited network’s mesh capabilities by setting up a mock network on one of the campus quads, and connecting at various locations.
# Solution Components
## Router and Wireless Access Point
Wireless Access for users and traffic routing will be the responsibility of an Omega2 board, with onboard Mediatek MT7688 CPU. For increased signal strength, the board will connect to a RP-SMA antenna via U.FL connector.
The Omega2 will be running OpenWRT, an Linux-based OS for routing devices. We will develop processes for the Omega2 to support our desired QoS features.
## Battery Management System
This module is responsible for charging the lithium-ion battery and ensuring battery health. Specifically, we will ensure the battery management system has the following features:
- Short circuit and overcurrent protection
- Over- and under-voltage protection
- An ADC to provide battery status data to the microcontroller
- 3.3v voltage regulation for the microcontroller and other sensors
In addition to miscellaneous capacitors and resistors, we intend to use the following components to implement the battery management system:
- The MT2492 step-down converter will be used to step down the output voltage of the battery to 3.3 volts. Between the GPS and extra power the microcontroller might consume with an upgraded Wifi antenna, low-dropout regulators would not provide sufficient power in an efficient manner. Instead, we will implement a 2 amp buck converter to improve efficiency and ensure there are no current bottlenecks.
- We will utilize two button-top protected 18650 3400 mAh lithium ion batteries in series to power each node. Placing two of these batteries in series will ensure their combined voltage never falls below the minimum voltage input of the buck converter, and accounting for the buck converter’s inefficiency these batteries should give us about 21 Wh of capacity. The cells we plan on using include a Ricoh R5478N101CD protection IC that provides over-voltage, under-voltage, and over-current protection. Using a standard battery form factor will make them easy to replace in the future as needed.
- A USB-C port with two pulldown resistors will provide 5 volt charging input with up to 3 amps of current, depending on the charger.
- The MT3608 step-up converter will boost the input voltage from the usb-c port and feed it into the charging controller.
- The MCP73844 Charge Management Controller will be used to charge the batteries. This controller supports CC/CV charging and a configurable current limit for safe and effective battery charging.
- The TI ADS1115 ADC will be used for battery voltage monitoring. This chip is used in the official Omega2 expansion board, so it should be easy to integrate in software. We will use a voltage divider to reduce the battery voltage to a range this chip can measure, and this chip will communicate over an I2C bus.
## Sensor Suite
Each node will have a battery voltage sensor and GPS sensor, providing the system with health information for each node. On top of the Wifi-connectivity, each module would have a series of sensors to detect the status of the physical node and helpful environment variables. This sensor suit will have the following features and components to implement it
- Ultimate GPS Module PA1616D will be used for positioning information. This chip utilizes 3.3V which is supplied through our battery management system.
Battery Voltage Monitor
- The TI ADS1115 ADC (mentioned in the BMS section) is for battery voltage monitoring. It interfaces via I2C to the Omega2.
## System Monitor
A system monitor which provides visibility of the overall system status for deployed network nodes. Information that we will show includes: last known location, battery health, and network statistics (e.g. packets per second) from the physical devices.
We plan on using React to provide an intuitive UI, using google-map-react and other React packages to create an interactive map showing the last known location and status of each node.
The backend will be hosted on a server in the cloud. Nodes will continually update the server with their status via POST requests.
# Criterion For Success
We aim to achieve the following performance metrics:
- 1.5 kg maximum mass
- Cover 7500 m^2 (North Quad) with 4 nodes
- Display the last known location, time connected, and battery voltage for all nodes via our system monitor
- 3 hour battery life
- 5 Mb/s WiFi available to laptops and smartphones in the coverage area
[*Link*](https://courses.engr.illinois.edu/ece445/pace/view-topic.asp?id=71252) *to assciated WebBoard discussion*