People safety is a major area of concern for many businesses. Thanks to the ability of devices such as mobiles and wearables to capture information and communicate, businesses can improve their level of preparedness for protecting their workers. IoT and Cloud technologies can be used to implement these effective yet inexpensive personal and workplace safety solutions .
Consider scenarios where people are working in mines, construction sites, dangerous terrains or participate in rescue operations – if they are caught up in some sort of emergency life threatening situation, and potentially lost communication contact with the outside world. The picture shown below is a schematic that one would expect such a solution to look like:
Many current generation smart phones, personal wearables such as fitness trackers, and smart watches have built in sensors that can capture a host of information such as temperature, humidity, atmospheric pressure, etc.
In this blog, we would like to provide a broad overview on the key components and technology architecture to build a safety solution. We can divide the solution architecture into three components:
- The process to quickly and precisely collect data of the incident, with minimal or no manual intervention.
- To share accurate information to the appropriate rescue/emergency response teams and help them launch rescue operations in the fastest time
- A monitoring system to track the current status and store all such previous incidents, so that we can use the data to analyse, identify causes and take appropriate precautions to ensure that they don’t reoccur in the future.
It will be helpful to use sophisticated sensors which have the ability to continuously capture critical information on the following parameters and communicate them to a base station from time-to-time:
- Atmospheric Pressure
- Light Intensity
- Presence of harmful gases
It could also be the case that multiple sensors can communicate with one another or with a central local network device. The central device or base station can have more intelligence than the device, which can be used to trigger an alarm. To establish communication, you could use a simple PHP/Java/.Net framework to process the request and send information to appropriate rescue/emergency response teams.
In addition to sharing the data generated through these sensors and devices with a base station, they can also be captured through a mobile app that can be deployed on Android and iOS platforms, which can be used to trigger an event. To trigger an event via the mobile app, Firebase can be used, which is a database for real-time sync, which helps to synchronize all the devices related to that site, with minimal effort.
Firebase and Firestore are popular offerings from Google and a lot of documentation is available in the public domain. The high-level architecture shown below can be used to quickly build a safety solution:
Adding a case management style workflow will make the application very powerful with collaborative decisioning. You can also use the insights to improve the business processes, especially the safety-related processes while integrating with these systems. Based on the type, location, and severity of the event intelligent rules can be applied for triggering an effective response.
A closed loop system with information flow from sensors to capture real-time data and identify events, process captured data and trigger a corresponding case flow for communicating either to a base station or to an emergency response team for launching rescue operations, adds automation and speed to personal safety solutions.
Other extensions to these solutions could be a pulse and/or heartbeat monitoring system, where a live connection is treated to be safe and a missed heartbeat or abnormal pulse can trigger alerts on potential incidents.
Real-time data capture through sensors and IoT provides enhanced visibility into working conditions and enables centralized teams to be on the lookout for signs of danger to their remote workers. You can not only leverage these technologies for triggering quick, reactive responses but also use predictive analytics to anticipate and prevent future incidents from happening.