Due to advances in technology and size reduction of portable mechanical and electronic devices, sensors
have been involved in many sectors, including in agriculture, where sensors and their unique functionalities
are extremely useful for both productivity gains and reducing operating costs. These benefits
are attained by utilizing their real-time sensing capability over environmental stages affecting the animal
breed to enable on-time decision support but with some limitations, i.e., mobility, coverage, ubiquitous
access, and energy. Thus, this research focuses on the integration of wireless sensor and mobile system
networks with a well-known sensor integration platform toward cloud offloading scalability services
via a hybrid architecture used to collect sensing data, such as temperature, humidity, light intensity,
and population density, for data analytics and then issuing on-time decisions to adjust the environmental
behavior accordingly. Based on a smart poultry farm concept for evaporative cooling environments, the
instrument and components of the system design are discussed in detail with the experienced selection
criteria, including a discussion of practical topology and deployments, enhanced transmission logics,
external environmental tuning control logics integrating mobile user management interfaces, and image
processing units. Aside from the proposed prototype of the integration of mobile phones, sensors, and
controllers, an experimental investigation was also performed on data sensing and transmission procedures
regarding power consumption characteristics, especially on high-cost image data transmissions,
including an illustration of the outstanding performance, i.e., 80% in accuracy with low computational
complexity, of the image filter over other well-known image classification techniques.