Internet of things based system for environmental conditions monitoring in poultry house: A case of Tanzania

Abstract

Poultry health is imperative for the continued growth of poultry and increased production. Environmental conditions such as temperature, humidity, and Ammonia gas impact the health of the poultry; whereby, they can affect the respiratory system and eventually cause death. In Tanzania, most farmers use charcoal and kerosene stoves to control these parameters as they have limited access to economical, secure, and user-friendly poultry house monitoring systems. However, such traditional methods are not environmentally friendly, unreliable, difficult to manage, and inaccurate. In addition to that, many smart poultry monitoring platforms proposed by previous studies are not centralized, thus making the system being not scalable and costly. For example a farmer with three distributed coops needs three monitoring platforms to monitor the coops while only single platform could suffice. Therefore, this study proposes an Internet of Things (IoT) based system for environmental conditions monitoring in the poultry house to address the aforementioned challenges. The survey was conducted in Arusha and Kilimanjaro regions respectively to determine the strength and weakness of the traditional methods used by poultry farmers, perception towards the proposed system and identify the requirements needed to develop the proposed an IoT based system. The study used Jupyter Notebook powered by Anaconda package manager and the Python language for data analysis. Based on the requirements gathered from the survey, the prototype that is divided into two four parts; sensing, aggregation, transmission and monitoring part was developed, where the hardware components were selected based on the cost, open source, availability in local market, Quality of Service (QoS), throughput and latency criteria. The developed prototype was deployed in the field to verify and validate its performance. This activity was done in seven days consecutively and the results indicated that the system would save both small scale and large scale farmers in terms of time and labor costs as Farmer can monitor and control the poultry house conditions securely, reliably, and remotely. The study also proposes an algorithm to allow the system to work online, and offline (i.e., synchronizing with the cloud server when the Internet access is available).