Internet of Things in Aquaculture: Challenges and Potentials

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By Milthon Lujan

Diagram showing how the components of an Internet of Things system interact. Source: Rastegari et al., (2023).
Diagram showing how the components of an Internet of Things system interact. Source: Rastegari et al., (2023).

The aquaculture industry has been promoting the adoption of new technologies to increase profitability.

In recent years, approaches such as precision aquaculture have been encouraged with the aim of ensuring profitability, sustainability, and environmental protection by incorporating innovative technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT) in aquaculture.

A team of researchers from the Institute of Tropical Aquaculture and Fisheries at the University of Malaysia, the ICT Organization of Isfahan Municipality, and the Universitas Sumatera Utara published a scientific review categorizing the challenges associated with the implementation of IoT systems in aquaculture.

The researchers reviewed IoT system prototypes reported in scientific literature over the past five years. Among the IoT systems used in aquaculture, some face common challenges, while others are specific to certain species or farms.

Challenges in IoT Implementation

Using scientific literature as a guide, the researchers identified two main categories of challenges:

  • Common challenges: general problems that can occur in most IoT systems, including aquaculture.
  • Specific challenges: covering challenges in different aspects of aquacultural activities, such as electricity scarcity, inadequate communication coverage, harsh environment, and inadequate technology.

Common Challenges

The continuous contact of sensors with water, which usually has a high organic load, reduces the accuracy of readings over time. To overcome this problem, the literature suggests regular maintenance of the sensors.

The incorporation of a sensor cleaning mechanism increases the overall cost of any IoT solution. However, it ensures accurate readings for the need of manual maintenance. The design of the cleaning system should not affect the sensor readings.

Specific Challenges

The researchers grouped specific challenges into three subcategories: infrastructure-related, data-related, and perception-related.


Challenges related to infrastructure mainly involve electricity availability and internet connectivity.

To overcome challenges related to electricity availability, the researchers suggest energy harvesting technologies (solar, wind), and for internet connectivity, they propose offline systems or satellite internet.


The quality of recorded data is crucial in IoT systems to facilitate decision-making. Many factors affect data quality from the data source (e.g., sensor quality) to the point of reception.

The subcategory related to data covers challenges related to data loss due to device or network errors.

Various studies have shown that incorporating diverse methods can help solve problems related to data loss.


Challenges related to perception examine the barriers that prevent aquaculturists from implementing IoT systems.

According to some studies, the overall perception of small-scale aquaculturists is that IoT is not useful in aquaculture. The lack of exposure to successful farm examples was the main reason.


As a potential solution to overcome the challenges, the scientific literature suggests that policymakers intervene to promote the benefits of IoT systems and provide incentives.

Farhad Nadi
Higher Institution Center of Excellence (HICoE), Institute of Tropical Aquaculture and Fisheries, University Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia
ICT Organization of Isfahan Municipality, Isfahan 8163654376, Iran
Email: farhad.nadi@gmail.com

Reference (Open Access)
Hajar Rastegari, Farhad Nadi, Su Shiung Lam, Mhd Ikhwanuddin, Nor Azman Kasan, Romi Fadillah Rahmat, Wan Adibah Wan Mahari. 2023. Internet of Things in aquaculture: A review of the challenges and potential solutions based on current and future trends, Smart Agricultural Technology, Volume 4, 2023, 100187, ISSN 2772-3755, https://doi.org/10.1016/j.atech.2023.100187.

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