Power, or lack thereof

After trawling the internet for some time, I still can’t seem to get a defnititve answer for my project requirement.

The requirement is to have accelerometer sensors connected to gym equipment and the movement data to be sent to the cloud for analysis. Something like below:

  • 50 - 100 accelerometer sensors
  • Connecting to hub (photon?)
  • Maximum battery life (Rechargeable? Disposable? 3 months of life? 1 Year?) Battery life very important
  • Collect data at central point (Raspberry Pi?)
  • Cloud analytics (Plotly? Log entry?)

I always get stuck on battery life and I understand this a ‘it depends’ answer. Is Photon the best approach?

@member01, what you don’t mention is whether the data is being streamed (always on) or only when the equipment is being moved. You also don’t mention the typical “ON” time of a sensor node and the how fast the accelerometer is being sampled and the amount of data being sent. Without a model for how the nodes and the network will operate, it is impossible to calculate a battery life estimate and provide advice on how to collect it.

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Thanks for your response and good points

  • The data will be streamed when equipment is in use, think of a sensor being attached to a dumb bell
  • The dumb bell would be in use around 4 hours per day, 7 days a week. Otherwise would be stationery
  • The data does not need to be highly accurate so sample rate would not be too high. Just need to see patterns between different gym attendees

Hope this clarifies things a bit.

@member01, 4 hours per day of sampling at, say, one sample every second to fit within the one-publish-per-second limit makes for 14,400 data points per day or more if sampling is more that than. I can assume that equipment will not be used solidly for 4 hours so if you were using a photon it would need to wake, connect to wifi and the cloud, send its data for the duration of the activity and go back to sleep. It could be sending data a lot or not. You need to characterize this. Predicting battery life under these conditions is impossible without a “model” and I suggest building a prototype to do testing.

Ultimately, you may need to consider using a lower power device like BLE, nRF24 or LoraWan. Each of these presents different challenges, especially with 50-100 devices.

Another approach you may want to consider is to have a simple BLE peripheral on each piece of equipment that announces the accelerometer data whenever it moves. These would be very low power. The gym member would wear a device with a battery that only needs to last for their time at the gym and can be recharged after each session. The device would have a Photon and BLE radio (eg. Redbear Duo or Photon/Bluz combo) and it would listen for the specific BLE announcements from the equipment, peel the accelerometer data from it and publish it to the cloud to be picked up by the rPi or other server. The challenge with the approach is to pick up only the nearest (being used) BLE device and not any adjacent ones.