The IoT Ecosystem, as depicted below in Figure 1, consists of Sensors, Gateways, Infrastructure, and of course, the flashy part of the IoT Ecosystem, Big Data and Analytics. A speaker at a recent IoT conference summed it up best with the statement “Big Data will be Big!”. The modeling of data supporting predictive analytics, whether it resides in the cloud or at the edge, gives organizations the ability to quickly diagnose and troubleshoot not only their sensor networks from a predictive maintenance perspective but also their operations, reducing excess use of energy and/or raw materials.
As Machine to Machine (M2M), Internet of Things (IoT), and of course, Industrial Internet of Things (IIoT) makes the transition from technology magazines to corporate strategic initiatives, companies are recognizing a significant opportunity to enhance productivity, efficiency, and profitability through Wireless Sensor Networks (WSN). These Networks have emerged as a key technology for oil & gas exploration and production companies looking to gain a competitive advantage. Since initially being introduced, manufacturers have enhanced product offerings to operate in the most inhospitable of environments while fortifying the technology with more robust communications architectures, hardening security, increasing reliability, and driving down power consumption. Through the entire oil & gas value chain (upstream, midstream, and downstream) as well as other industrial markets including Electric Power, Water/Waste Water, and Manufacturing, wireless sensor networks are increasingly being deployed where hardwiring was the De facto standard.
For many industrial applications, it has been well documented that wirelessly connected assets are up to 10X less expensive than wired alternatives. Driven by
substantial and measurable cost savings in engineering, installation, and logistics as well as dramatic improvements in the frequency and reliability of data, wireless sensor networks offer much faster startups, and accelerated profits.
Wireless sensor networks fit within the context of Machine to Machine (M2M) Communications referring to direct communications between devices. More recently,
the discussion is often via the Internet of Things (IoT). The concept of IoT was first introduced by Kevin Ashton in 19991 and refers to uniquely identifiable assets and their organizational “internet-like” structure. These assets can be anything but in the industrial automation world, it is specific to wireless sensors. While IoT does not define communication platforms or topologies, wireless sensor network communications architecture implementations allow for the proliferation of the technology across all markets and applications.
A wireless sensor network can be defined as a network of end nodes communicating information gathered from sensor locations through wireless links. Depending on the communications architecture, the data is either forwarded directly to a Gateway or perhaps through multiple end nodes back to a Gateway. The Gateway is then connected to other devices or networks such as a wired or wireless Ethernet backbone to relay sensor information to a control system. These networks are used to monitor a variety of conditions, covering all process control variables regardless of vertical market, including but not limited to Pressure, Flow, Temperature, and Level.
For the wireless communications piece, the sensor network end nodes are organized based on the topology implemented. By far, the two most common implementations are a Star topology and a Mesh topology (depicted in Figure 1). The Star topology is a single hop from the end node communicating directly to the gateway and the simplest wireless sensor network topology. Theoretically, these systems are considered the most reliable as there is but one single point of failure – the gateway. In a Mesh topology, the Gateways and end nodes work together to form a Mesh network where data from the sensor is relayed through the network to reach the gateway. A Mesh topology can be self-organizing and as a result, does not require manual configuration. For a wireless sensor network with closely located assets, this topology is inherently reliable and scalable.
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