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A LoRa-based Energy-efficient Sensing System for Urban Data Collection

Lukas Schulthess, Tiago Salzmann, Christian Vogt, Michele Magno

TL;DR

The paper addresses the need for privacy-preserving, continuous data on public-space usage to inform urban planning. It proposes a LoRaWAN-based edge sensing system that measures chair occupancy via a threshold-based sitting detection on an accelerometer, along with environmental sensing (noise, temperature, humidity) and GNSS location, all duty-cycled to save energy. In a two-month field trial in two city squares with 16 nodes, the system achieved 33.65 mWh/day and demonstrated practical insights into space utilization, despite 5 nodes being vandalized. Open data availability supports transparency and replication for urban planners and researchers.

Abstract

Nowadays, cities provide much more than shopping opportunities or working spaces. Individual locations such as parks and squares are used as meeting points and local recreation areas by many people. To ensure that they remain attractive in the future, the design of such squares must be regularly adapted to the needs of the public. These utilization trends can be derived using public data collection. The more diverse and rich the data sets are, the easier it is to optimize public space design through data analysis. Traditional data collection methods such as questionnaires, observations, or videos are either labor intensive or cannot guarantee to preserve the individual's privacy. This work presents a privacy-preserving, low-power, and low-cost smart sensing system that is capable of anonymously collecting data about public space utilization by analyzing the occupancy distribution of public seating. To support future urban planning the sensor nodes are capable of monitoring environmental noise, chair utilization, and their position, temperature, and humidity and provide them over a city-wide Long Range Wide Area Network (LoRaWAN). The final sensing system's robust operation is proven in a trial run at two public squares in a city with 16 sensor nodes over a duration of two months. By consuming 33.65 mWh per day with all subsystems enabled, including sitting detection based on a continuous acceleration measurement operating on a robust and simple threshold algorithm, the custom-designed sensor node achieves continuous monitoring during the 2-month trial run. The evaluation of the experimental results clearly shows how the two locations are used, which confirms the practicability of the proposed solution. All data collected during the field trial is publicly available as open data.

A LoRa-based Energy-efficient Sensing System for Urban Data Collection

TL;DR

The paper addresses the need for privacy-preserving, continuous data on public-space usage to inform urban planning. It proposes a LoRaWAN-based edge sensing system that measures chair occupancy via a threshold-based sitting detection on an accelerometer, along with environmental sensing (noise, temperature, humidity) and GNSS location, all duty-cycled to save energy. In a two-month field trial in two city squares with 16 nodes, the system achieved 33.65 mWh/day and demonstrated practical insights into space utilization, despite 5 nodes being vandalized. Open data availability supports transparency and replication for urban planners and researchers.

Abstract

Nowadays, cities provide much more than shopping opportunities or working spaces. Individual locations such as parks and squares are used as meeting points and local recreation areas by many people. To ensure that they remain attractive in the future, the design of such squares must be regularly adapted to the needs of the public. These utilization trends can be derived using public data collection. The more diverse and rich the data sets are, the easier it is to optimize public space design through data analysis. Traditional data collection methods such as questionnaires, observations, or videos are either labor intensive or cannot guarantee to preserve the individual's privacy. This work presents a privacy-preserving, low-power, and low-cost smart sensing system that is capable of anonymously collecting data about public space utilization by analyzing the occupancy distribution of public seating. To support future urban planning the sensor nodes are capable of monitoring environmental noise, chair utilization, and their position, temperature, and humidity and provide them over a city-wide Long Range Wide Area Network (LoRaWAN). The final sensing system's robust operation is proven in a trial run at two public squares in a city with 16 sensor nodes over a duration of two months. By consuming 33.65 mWh per day with all subsystems enabled, including sitting detection based on a continuous acceleration measurement operating on a robust and simple threshold algorithm, the custom-designed sensor node achieves continuous monitoring during the 2-month trial run. The evaluation of the experimental results clearly shows how the two locations are used, which confirms the practicability of the proposed solution. All data collected during the field trial is publicly available as open data.
Paper Structure (8 sections, 8 figures, 2 tables)

This paper contains 8 sections, 8 figures, 2 tables.

Table of Contents

  1. Introduction
  2. System Definition
  3. Hardware Architecture
  4. Firmware
  5. Experimental Results
  6. Power Consumption
  7. Data combination and Evaluation
  8. Conclusion

Figures (8)

  • Figure 1: System-wide overview of multiple sensor nodes connected to the server back-end over LoRaWAN gateways.
  • Figure 2: High-level architecture of the proposed sensor node, divided into the three main sections communication and processing (blue), environmental sensing (green, and power distribution (red).
  • Figure 3: Task activity of the sensor node, arranged according to sampling intervals (1-4). At sampling interval 4, temperature and humidity are sampled and transmitted together with all other measurements via LoRaWAN.
  • Figure 4: An installed sensor node attached to a public chair on an urban square. Experimental results have shown that cases with white coating have a lower internal temperature of approximately 10℃ when compared to black casings.
  • Figure 5: Power consumption of the designed sensor node over time in 3 different modes: Standby and sitting/noise detection (a) and GNSS recording and LoRaWAN transmission (b). For each operation mode, the average power draw (Avg) is given.
  • ...and 3 more figures