Trillions of bytes of data are sent and received across the Internet every day. Unfortunately, many networks are limited by local connection and storage points, resulting in slower speeds and service interruptions. Intellisense Systems is using edge computing to ensure weather and water level data are received at their destinations swiftly and reliably.
Edge computing involves the speedy, efficient transfer of data by physically processing it closer to its source. To achieve this, it employs a network of servers, IoT-devices, and nodes that distribute and lower the amount of processing, power, and time needed to transmit data. It is a helpful and, in many cases, necessary part of transmitting and storing data.
While cloud-based servers have tremendous processing capabilities, they require all source data to be delivered all the way from the edge of the network to the servers. By placing more processing power on the sensor devices at the edge of the network, data sent to servers can be greatly reduced. While this movement from the center of a network (i.e. at the server) to the edge of a network can increase power demands at the sensor, it reduces data throughput demands in the network, making it far more efficient.
The practice of edge computing promises many benefits beyond saving bandwidth and improving upload/download speeds. By leveraging devices at the edge of the network, people and organizations can reduce the latency, power consumption, and costs of transmitting data. It also presents opportunities for some valuable network enhancements:
- Efficiency: The addition of devices or nodes at the edge of a network can greatly improve capacity and transmission speeds. By using servers located on a local edge network, files only need to be processed and transferred locally. Avoiding transmission over cellular networks also reduces the amount of bandwidth needed.
- Scalability: The placement of small devices or nodes at network edges also offers greater potential for scalability. Rather than housing servers in large facilities that are limited by space, edge computers are nimbler, consume less power, and enable data to reach its destination faster.
- Reliability: In some cases, edge computers bolster network reliability through multiple backup devices and nodes. This does require a physical topology of network devices to be mapped, and the dependability of edge-based devices may depend on environmental conditions.
- Security: Even though edge-based devices are susceptible to tampering and may not receive every software update over the course of their lifespans, they do put security in the hands of end-users rather than service providers. This practice could protect end-users from large data breaches. In addition, edge-based devices may enable special encryption mechanisms for improved security.
Though it does have many benefits, edge computing does present a few obstacles and challenges. The first is the potential for limited capacity, which could result from the amount of data processed or the number of service providers relying on edge-based devices. There are environmental limitations to edge computing as well. Unlike large server farms in climate-controlled structures, edge computers may need to withstand environmental hazards in remote areas like inclement weather and wildlife.
But as 5G and cloud-based services increase, organizations and communities need edge computing to deliver essential services. Environmental sensors from Intellisense Systems leverage edge computing capabilities to ensure that key weather and water level data is reliably stored and transmitted for these essential operations. The Micro Weather Station (MWS®) collects and transmits over 20 environmental parameters thanks to on-board edge computing that stores weather data in a cloud-based data logger.
The AWARE Flood System also sends environmental data and images via a network of nodes, so they do not need to rely on existing networks to transmit data. The hardware inside these nodes reliably report water level and precipitation data to alert users to flood risk. They use integrated solar power systems with built-in battery packs for sustained operations in remote areas, and they are ruggedized to withstand nearly every environmental hazard.
Edge computing capabilities in environmental sensors from Intellisense have already been a vital part of numerous applications. For instance, renewable energy projects have greatly benefited from the cloud-based storage and data reporting features of both the MWS and the AWARE Flood System. Wind farms and geothermal stations deliver power to rural areas and reduce CO2 emissions by hundreds of thousands of tons every year. They use the cloud-based and edge computing data logging of the MWS to receive important weather data for their operations. Similarly, hydropower is generated via dams that are located upstream from urban infrastructure, and they need water level and precipitation data to make sure that dams are not breached. The network of AWARE Flood System nodes keeps decision-makers and personnel alert to water level and the risks of flooding.
Those are just some of the ways in which sensors from Intellisense are bringing the benefits of edge computing to a number of important applications. Uses as far ranging as traffic cameras to drone operations to rural airports can benefit from edge-based computing. As these energy-saving and infrastructure-enhancing projects grow in the coming decades, Intellisense can reliably and swiftly supply essential data through the edge-computing properties of its advanced and innovative environmental-sensing solutions.