Data collection is an essential part of sensor devices, particularly in such technologies Like Internet of Things (IoT), wireless sensor networks (WSN), and sensor cloud (SC). In recent years, various literature had been published in these research areas to propose different models, architectures, and contributions in the domains. Due to the importance of efficient data collection regarding reducing. energy consumption, latency, network lifetime, and general cost, a momentous literature volume has been published to facilitate data collection. Hence, review studies have been conducted on data collection in these domains in isolation. However, a lack of comprehensive review collectively identifies and analyzes the differences and similarities among the data collection proposals in IoT, WSN, and SC. The main objective of this research is to conduct a comprehensive survey to explore the current state, use cases, contributions, performance measures, evaluation measures, and architecture in the IoT, WSN, and SC research domains. The findings indicate that studies on data collection in IoT, WSN, and SC are relatively consistent with stable output in the last five years. Nine novel contributions are found with models, algorithms, and frameworks being the most utilized by the selected studies. In conclusion, key research challenges and future research directions have been identified and discussed.

In recent years, Wireless Sensor Networks (WSNs) technologies are used in many important areas, including weather forecasting, security, environmental monitoring, health care, and industry. Nonetheless, due to the constraints of WSNs in terms of energy, processing, connectivity, computation and data integrity. An important issue in this research field is the efficient management of the large number of WSN’s data. Therefore, there is a need for strong and scalable high-performance computing and large storage infrastructure for real-time processing and storage of WSN’s data. This article attempts to discuss data collection methods in WSNs, sensor cloud, and IoT. Also, in this context, a general overview of WSNs and sensor cloud platforms, including their definitions, architectures, and applications are given. We investigate, highlight and report recent advances in data collection technology by categorizing and classifying data collection methods in WSNs, sensor cloud, IoT and developing a taxonomy based on these classifications. Furthermore, the analysis and synthesis of existing works in this research domain is highlighted. The identification of key research challenges for future work and use case in this research domain were also highlighted and discussed.

The integration of cloud computing and Wireless Sensor Networks (WSNs) to create Sensorcloud helps in extending the data processing capability and storage capability of WSNs. Knowing how weak WSNs are with regards to communication ability, how to collect and upload sensory data to the cloud in limited time has become an issue in Sensor-cloud. In the last decade, with increasing interest by researchers in the domain, a considerable amount of research works have been conducted and published in the research domain. The main objective of this study is to systematically review the current research on data collection in Sensor-cloud. Hence, the study also aims at identifying, categorizing, and synthesizing important studies in the field of study. Accordingly, an evidence-based methodology is utilized in this study. By doing so, 43 relevant studies were identified and retrieved to answer the formulated research questions. The systematic methodology offers a methodical and rigorous study selection and evaluation process that is repeatable and precise. The result shows that research on data collection in Sensor-cloud is relatively consistent with stable output in the last five years. Ten proposal contributions were identified with System, Framework, and Algorithm being the most used by the selected studies. In conclusion, key research challenges and future research directions were identified and discussed for researchers to propose effective solutions to the existing challenges. Although research on data collection in Sensor-cloud is gaining some traction in recent years, the works in the domain are not sufficient and concrete proposals are needed to improve data collection.