## 2 Review of Related Works
However, fostering trust between the government and citizens remains a key challenge in driving IoT adoption in e-government initiatives. The agricultural sector, particularly in developing regions, has also embraced IoT applications to improve productivity and resource management. In South Africa, [PERSON] et al. [17] explored factors such as organizational support and knowledge gaps that influence IoT adoption in smart agriculture. Similarly, [PERSON] et al. [33] in the US identified technical barriers such as data latency, scalability, and sensor compatibility. These studies indicate that the IoT can play a transformative role in agriculture, but addressing technological constraints and improving farmer awareness and training are essential for successful adoption. The construction industry offers another unique application area for the IoT, with the potential to improve efficiency and safety in construction projects. In China, [PERSON] et al. [32] investigated factors influencing IoT adoption by construction companies, identifying external environmental pressure and top management support as significant factors. In Rwanda, [PERSON] et al. [16] found that a lack of IoT awareness and poor internet connectivity were major challenges in the construction industry. Both studies emphasize the importance of leadership support and infrastructure development in driving IoT adoption in construction. The review of related works across these application areas reveals common themes in IoT adoption, such as concerns over privacy, security, and infrastructure. However, the specific challenges vary by sector and region, with industries like healthcare and education focusing on trust and usability, while sectors like agriculture and construction emphasize technological readiness and organizational support. These insights emphasize the need for sector-specific strategies to address the barriers to IoT adoption and fully leverage its potential across different industries and market segments. While the IoT has attracted significant attention as a transformative technology across various sectors, existing studies primarily focus on sector-specific IoT adoption in areas such as smart cities, education, healthcare, and agriculture, often in more developed regions. Despite these insights, there remains a critical gap in the literature concerning IoT adoption within emerging technology ecosystems, particularly in the underexplored Central African region. No comprehensive study has examined the factors influencing IoT adoption in technology ecosystems within the Central African region, particularly within innovation clusters like Silicon Mountain. This gap is critical, as the region presents unique barriers (e.g., infrastructure limitations, skill gaps, and regulatory challenges) that are distinct from those found in more developed ecosystems. Understanding these region-specific factors is essential for fostering IoT innovation and growth, yet the absence of targeted research on IoT adoption in Central African technology ecosystems leaves policymakers, industry stakeholders, and academic institutions without the necessary data to inform strategic decision-making. While global studies, including those from international organizations such as the World Bank, Internation Telecommunications Union (ITU), and African Development Bank, have provided valuable insights into the challenges of IoT adoption in developing regions, such as sub-Saharan Africa, there remains a critical need for region-specific studies that address the distinct socio-economic, infrastructural, and regulatory conditions of Central African ecosystems like Silicon Mountain. For example, the World Bank and ITU reports have highlighted common barriers, such as inadequate infrastructure, skill gaps, and regulatory challenges, that are relevant to many African regions [34; 35]. However, these global frameworks and findings often provide macro-level data that may not fully capture the unique nuances of smaller technology ecosystems in Central Africa.