December 6, 2024

Industrial IoT and Other Edge Computing Applications

Edge computing brings computing closer to remote assets, decreasing dependence on connectivity with the cloud and enabling real-time analytics with minimal latency.

Edge-based systems can analyze data from security devices on site to enforce COVID-19 pandemic policies, or help a manufacturing company monitor production.

Industrial IoT

Industrial IoT (IIoT) allows companies to enhance processes and operations for improved efficiency, productivity and safety. Teams are able to monitor device and asset status across networks as well as identify potential vulnerabilities quickly to counter cyber attacks at an earlier stage.

IIoT helps manufacturers reduce production costs by automating tasks and reducing manual labor, while also identifying errors or issues that humans miss and alerting teams when machines require repairs – leading to significant savings on labor, product loss and downtime.

Industrial IoT allows managers to remotely access equipment and modify settings, saving on technician costs while improving worker safety by alerting of unsafe conditions (for instance when equipment becomes too hot, doors remain unlocked, machine usage drops etc.) It also tracks machine utilisation levels; alerting teams if equipment remains underutilized leading to increased performance, reduced maintenance expenses and greater productivity.

Smart Cities

Smart cities collect data from various sources to optimize energy use, transportation, security, water and waste management – ultimately reducing congestion, pollution, making streets safer to navigate, improving quality of life for residents and improving quality of life for them.

Connected street cameras can identify and track people’s movements, decreasing the risk of accidents. Meanwhile, smart parking lot occupancy detection can save drivers time and reduce traffic congestion by monitoring real-time space utilization data sent directly from parking lots to traffic control centers.

Smart sensors play an essential role in preventing critical infrastructure failures. By collecting information about structural changes such as tilts or cracks in buildings, bridges and roads that could result in catastrophe, smart sensors provide data on any necessary remedial actions before disasters strike – saving both tax dollars and lives by detecting problems early. Cutting-edge AI capabilities allow sensor location computer vision use instead of sending video streams back to central control rooms for encoding, analyzing, processing etc.

Health Care

Edge computing in healthcare can facilitate faster diagnoses by storing and processing patient data locally instead of depending on cloud servers for analysis. Furthermore, edge computing makes sharing information simpler between remote medical staff members in real time.

Furthermore, this technology helps prevent the spread of diseases by monitoring patients in real time and alerting emergency hospital physicians immediately of potential risks. Furthermore, this device can track pharmaceutical drugs to help identify counterfeiting or tampering incidents within supply chains.

As healthcare data is sensitive, its storage should be managed using low-powered and secure technology. A simple authentication mechanism should be utilized before connecting IoT devices to an Edge server and using an SDN controller can further ensure scalability and optimized performance in an Edge network, helping reduce end-to-end latency as well as security risks significantly.

Electric Vehicles

Electric vehicles produce multiple forms of data that must be quickly processed to support in-vehicle processes and dispatcher insights, says Arnie de Castro, principal product manager of industry products at SAS. Edge computing can quickly aggregate and send specific pieces of information needed without wasting bandwidth or creating delays, according to him. Such processing could also benefit public transit systems that need to disseminate timely information to passengers as well as lighting controls that need instant updates on status changes or intelligent lighting controls.

Enterprises are increasingly turning to edge computing to meet their business needs, such as meeting low-latency content delivery for over-the-top streaming services. Edge computing also plays an integral part in optimizing car charging stations by collecting and analyzing data at source to eliminate range anxiety and enable battery-to-grid energy management, while improving passenger experience through infotainment systems, augmented reality apps, mobility apps or machine learning models for advanced analysis of sensor or user behavior data.

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