AutoSafe goal is to provide a safe construction site. We are looking to integrate safety monitoring systems using Internet of Things (IoT) sensors. The IoT sensors connect to each other, and their main tasks are to gather important data and send it via internet protocol. The data gathered by these sensors give an insight into the condition of the construction site. For example, vibration data can indicate defections in structures, and temperature and humidity sensor readings can indicate if there is a heatwave. These data are also essential for alerting workers that are in potential danger. For example, if a gas sensor in a confined space detects an enormous amount of toxic gas, the system will alert the workers to evacuate immediately.
Installing sensors in construction sites, however, is not simple. First, construction sites constantly change depending on the stage of the construction. Wireless IoT sensors are preferred here as they can be easily installed and removed compared to their wired counterpart. Second, most construction sites provide minimal power supply, which can be solved by simply powering the sensors with portable batteries. Thus, wireless sensor technologies are much more preferred because of the complexity of construction sites.
In the field of IoT, edge computing is essential to filter and pre-process data so it can reduce network traffic by only sending relevant data. However, edge computing requires additional computational power, which can quickly drain the battery of these wireless sensors. As AutoSafe wants to focus on automating safety with minimal human interaction, we aim to preserve as much battery power as possible to reduce the frequency needed for the workers to change these sensors’ batteries.
Hence, we want to share a research paper written by one of our members on how to minimize battery consumption of edge computing IoT sensors. Three strategies are presented in the study:
1. Reducing the connectivity settings of the wireless network to reduce current consumption.
2. Managing the operation of the edge computing features
3. Adding more batteries via parallel connection
The study shows a massive improvement in the sensor lifetime from 20 days to 150 days (650% increase) using all three strategies. This means the workers only need to change the batteries every five months instead of every three weeks. The paper also proposes a generic flowchart summarizing the decision criteria for recommending how to choose and implement the strategies, according to the characteristics of different site monitoring applications.
(Source: Michael Abner, Peter Kok-Yiu Wong, Jack C.P. Cheng, Battery lifespan enhancement strategies for edge computing-enabled wireless Bluetooth mesh sensor network for structural health monitoring, Automation in Construction, Volume 140, 2022, 104355, ISSN 0926-5805, https://doi.org/10.1016/j.autcon.2022.104355)