The application of technology to aquaculture has been increasing, allowing for improved growth and health in many aquaculture species. For shrimp, the implementation of passive acoustic feed management in conjunction with automated aeration controls tied to dissolved oxygen (DO) monitoring has led to major improvements in production. These technological tools aim to improve decision-making but are limited due to the per-unit cost of collecting data. Quite often, these environmental records are limited to a particular unique point (s) this limited data is then used to extrapolate the environmental conditions for the entire pond. For example, a single DO reading at the effluent of a 10 Ha pond may be used to “extrapolate” DO levels of the entire pond. Because of cost and/or labor requirements, little work has been done to evaluate diurnal trends in temperature and DO across a wider area of ponds to map shifts in temperature and DO. An alternative to DO recording using internet of things (IoT), independent DO and temperature loggers are available (e.g. miniDOT® logger), which are less expensive and can be deployed for monitoring purposes. Hence, in addition to continual DO monitoring slaved to aeration management we deployed in four ponds, one extra monitoring DO sensor that does not need loT infrastructure, placing the sensor in the shallow end of the pond. We monitored the oxygen and temperature trend in these four ponds over 60 days of culture. Then, four Mini Dots were then deployed in one of those ponds to monitor DO over 16 days before harvest to track D.O across pond locations. During the draining process for harvest, one miniDoT was placed next to the optical sensor to evaluate DO, right before harvest. The results indicated no significant difference in DO concentrations in the shallow end (p>0.05) compared to the optical sensor deployed in the feeding area. In the 16 days when four sensors were deployed in one pond, no significant differences were found across pond locations. However, when ponds reached 25% of the volume, the hypoxia conditions increased. In small ponds such as the 0.1 ha research ponds, one water quality sensor might be enough to understand oxygen dynamics for the entire pond. However, in large ponds, DO are more likely to vary across the pond area, as water mixing is likely insufficient.