The aquaculture industry has seen exponential growth due to increased consumption of healthier proteins. Fish farms now shoulder most of the responsibility of meeting global supply as wild-caught fishing has not been able to scale to meet demands.
Despite technological advancements, aquafarms still grapple with production instability, fish loss, lack of efficiency, and inflated operational costs. To overcome the obstacles impeding aquaculture operations, IoT edge computing is well poised to enhance existing aquaculture software by increasing the speed, lowering lag time, and ensuring greater reliability of precious data needed for critical operations.
What Is IoT Edge Computing?
IoT edge computing comprises connected physical devices that produce data and an IoT gateway that serves as a conduit to route the data between the devices and the cloud. The connected physical devices act as small data centers and may include IoT sensors, industrial machines, routers, etc.
These components can be integrated with existing software through custom APIs and programmed to work together to collect, process, and transfer data over a network in a continuous loop. The physical hardware serves as a local source where data processing and storage occur to facilitate faster, near-real-time responses and improve overall efficiency.
Having this processing power closer to where the data source is located is beneficial because the data produced by an IoT-connected device is more efficiently transmitted and delivers more actionable insights when it is analyzed at the “edge” rather than having to reach a central database before it can be interpreted.
The localized source is in proximity to the devices generating the data, resulting in faster response times, sustained data volume and velocity, boosted performance, bandwidth, reliability, and security. Edge computing also facilitates the processing and storing data without intermittent connection disruptions that can occur with cloud computing.
IoT Edge Computing Expands Abilities in All Areas of Aquafarming Operations
Implementation of IoT edge computing expands the capabilities of aquaculture software, solving longstanding industry challenges and resulting in streamlined practices related to aquafarming and aquaponics environments.
Aquaculture IoT Sensor Technology
IoT sensors work by interpreting data and converting it into electrical signals. These electrical signals are emitted in response to the collected data and convey the size and scale of the monitored conditions. These sensors detect and measure specific conditions in an aquafarming environment and provide valuable insights to aquafarmers.
IoT sensors are programmed to monitor temperature, humidity, heat, pressure, light, sound, movement, and environmental factors, such as detecting the presence of a specific liquid, chemical, or gas, and measuring water quality. For example, sensors can measure the level of liquid compared to a set normal value in a signal. They can also be programmed to act as an alarm when levels fall outside of normal ranges.
Leveraging IoT Data in Aquaculture Software
Integrating IoT hardware back to any software system for aquafarming operations gives fish farms huge insights and decision-making capabilities.
Aquaculture Monitoring
Fish hatchery populations can be easily monitored and tracked using level sensors, chemical sensors, and water quality sensors to monitor chemical presence, oxygen levels, electrical conductivity, pH levels, salinity, and turbidity levels. Additional IoT sensor integration with aquafarm management software will provide the capability to track behavior, maintain egg-to-sale traceability charts, and offer cost analysis tools.
Aquaculture Artificial Intelligence
Artificial Intelligence (AI) can be utilized to improve analyses of aquaculture populations at the individual, batch, breed, site, and operational levels. These solutions can provide near-real-time assessments and valuable insights to improve aquatic conditions, feed amounts and schedules, extraction processes, and more. Additionally, fish farming apps can be interfaced with embedded ID tag software and used to study fish population data by age, gender, and other specific characteristics to provide valuable data analysis.
Fish Farm Management
Track aquatic lifecycles from hatcheries and nurseries using optical, proximity, motion, and other sensors integrated with custom aquafarm management software. These solutions can include integrated apps that are modified to include tools for larvae weaning, brood stock database analysis, and feed management.
Aquaculture Workflow and ERPs
Workflow management tools that include GPS trackers can be used with Enterprise Resource Planning (ERP) software to streamline operational processes encompassing site management and maintenance, asset tracking, feeding, harvesting, grading, and commerce.
IoT Edge Computing Produces Valuable Insights to Improve Fish Farm Decision Making
Programming and integrating embedded software and firmware such as IoT sensors, microcontrollers, processors, and gateways into IoT and M2M devices are essential to gain valuable information that will influence critical decision-making. Customizable features offered through IoT edge computing are used to provide tailored solutions that meet the specific needs of any aquaculture facility. These solutions have greatly reduced production costs, increased profitability, and streamlined processes.
Author Bio
Tyler Boykin is the Vice President of Sales at Chetu, Inc., a global, custom software development company, where he oversees the Hospitality & Travel, Food & Beverage, Agriculture, Transportation, and IT Service Management accounts, as well as a myriad of partner tools. A graduate of the University of West Georgia, Tyler joined Chetu in 2013 where has risen through the ranks of the sales department and helped the company grow into an award-winning organization.
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