## 1 Introduction  
Digital agriculture is defined as the modern application of information and communication technologies (ICTs) in agriculture to solve food insecurity problems [1, 2]. As the Food and Agriculture Organization of the United Nations (FAO) report on food insecurity and urbanization points out, the rate of urbanization is expanding rapidly. By 2050, almost 7 out of 10 people are expected to be living in cities, leading to changes in agri-food systems across the rural-urban continuum [3, 4]. This situation raises the challenge of how to increase the agricultural yields for an ever-growing population and to mitigate climate change issues [5]. To address this challenge, countries need to move towards precision agriculture. At the same time, agricultural systems constitute the main source of environmental problems in general and air pollution in particular. These problems induce a global health crisis [6, 7]. Indeed, ambient air pollution constitutes a relevant common health disorder, with models and monitoring data indicating a tremendous concentration of pollutants [8]. In order to raise awareness and engage in dialogue with stakeholders on the consequencesof air pollution, pollutant levels must be measured, and the data collected and processed must be accessible. Traditionally, data are collected using high-cost solutions that are not really accessible for low- and middle-income countries like most African countries. The development of emerging technologies came to break down these rules by introducing low-cost air quality sensors, a novel and cheaper approach to measuring pollutants. Recent technological advances offer opportunities for Africa to monitor and protect the environment, as well as the overall planetary health, and produce enough food to keep pace with a growing population. Healthier worldwide environments could prevent almost one quarter of the global burden of disease [9]. Many digital technologies are proposed to fill these requirements. Nowadays, IoT, Data Science, Big Data and Artificial Intelligence are the most proposed to assume the trade-off between raising farm productivity and maintaining healthier environments [10]. While IoT is the most used technology to collect and record agricultural and environment data, the others are mainly useful for data analysis and prediction [11]. IoT is defined as an interconnection of physical devices, vehicles, appliances and other physical things that are enclosed with sensors, software and network connectivity, which allows them to gather and share data [12; 13]. It presents several advantages, including real-time access to information, improved monitoring using sensors and machine-to-machine communication. IoT technology has transformed the agricultural and environmental industry by furnishing producers with the real-time information on crop state, soil moisture, weather conditions and pollutants [14]. This information can be used to enhance crop yields, diminish waste, enhance sustainable development [15] and inform environmental stakeholders, improving environmental conditions in Africa in general and West Africa in particular [16; 17]. IoT is in its early stage in West Africa, but many works are in progress or already performed concerning its application in both the agriculture and environment sectors. However, there is a lack of scientific review studies simultaneously in both sectors. To the best of our knowledge, none of the existing papers perform a comprehensive systematic review on IoT case studies in agriculture and environment in the West African region. This document aims to fill this gap. More specifically, our goal is to investigate existing works and extract relevant insights through both a quantitative study (most involved countries and universities, works production over time, etc.) and a qualitative study (use cases, IoT communications technologies used, types/costs of sensors, measured parameters, additional technologies used).