ORCID
0000-0003-0212-1466
Abstract
The growth of digital technology is expected to transform small-scale fishery sectors, where a need for robust, low-cost, long-range communication networks becomes critical. There exist several technologies that are used in the fishery sector but they are never affordable to small scale fisheries. This study evaluates the feasibility of using low cost Long Range Wide Area Network (LoRaWAN) technology specifically tailored for smart fishing environments to small scale fishery sector. Using simulation, we assess the performance of the key performance metrics including probability of success and energy efficiency under varying device densities and time. During evaluation, we considered end devices distributed in a rectangular shape with one gateway and two gateways archtectures. We have evaluated the performance of both standard and Time Division Multiple Access (TDMA) LoRAWAN in both one and two gateways configuration. The results showed that the probability of delivering packets successfully is high when there are fewer devices in the network for both models. However, there is a significant drop in standard LoRaWAN when the number of devices increases as they contend for the channels unsuccessfully. It was demonstrated that TDMA approach significantly outperforms standard ALOHA in high-density scenarios, maintaining a 1.0 success probability. While the network exhibits high reliability for non-critical data across distances up to 10km, the consistent 20-second latency suggests limitations for time-sensitive emergency alerts.
Recommended Citation
Shayo, E. (2026). On the use of LoRAWAN for Smart Fishing Applications in the Blue Economy Sector. Tanzania Journal of Engineering and Technology (TJET), 45(1), 104-110. https://doi.org/https://doi.org/10.65085/2619-8789.1090
Publisher Name
University of Dar es Salaam
Included in
Artificial Intelligence and Robotics Commons, Controls and Control Theory Commons, Electronic Devices and Semiconductor Manufacturing Commons, Thermodynamics Commons, Transportation Engineering Commons