Perhaps the most visible technological advance underlying the Industrial Internet is the widespread adoption of networked sensors and actuators. Sensors and their embedded software logic are rapidly becoming ubiquitous, permeating every corner of the physical world. For example, availability of sensors are enabling the transformation of farming into the complex field of precision agriculture that increasingly relies on IT systems to drive the way our crops are grown and our fields are maintained. Similarly, Oil and Gas Pipelines are critical infrastructures that need to be continuously monitored to ensure that they are in service. Any loss of service can result in significant financial or environmental loss. Most petroleum producers recognize the importance of deploying an effective pipeline monitoring and surveillance solution to ensure this. Sensors have been embedded in existing pipelines for maintenance, diagnostics, and repair.
With large numbers of sensors already placed in these critical infrastructures, collecting data from these sources efficiently becomes a problem. The current process is people intensive and therefore costly. Additionally, the cost of retrofitting these infrastructures with network connectivity is cost prohibitive.
Successfully deployed in commercial demonstrations during the past few years, Unmanned aerial vehicles (UAVs) – also known as drones - have shown early signs of strong business value in several applications. In most applications, the UAVs have been used as a platform to carry different types of payload. The typical payload has been various types of cameras for aerial photography. In addition, in some experiments the UAVs have also been outfitted with sensors such as gas detectors, temperature, etc. Perhaps even more compelling is the use of the UAV to carry a network gateway payload which enables network connectivity, and serves as a sensor reader and aggregator that can collect readings from sensors deployed in the infrastructure.
In this deployment model, the UAV is equipped with a payload consisting of a specialized gateway box. The gateway box with a controller, a sensor reader, a Wifi network, a proximity sensor and a 3G network. As the UAV follows its flight path, the proximity sensor detects the availability of a sensor in its path and triggers a network connection to the remote sensor. The controller then proceeds to read the sensor and either stores it locally if no 3G network is available or forwards it to the cloud if the 3G network is available. Once the data is in the cloud, it is available for further analysis and processing by back end operations.