# Recent Advancement of Data-Driven Models in Wireless Sensor Networks: A Survey
## 5 Analysis of Data-Driven Models for WSNs
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\begin{tabular}{p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt}} \hline \hline
**References** & **Applications** & **Data Models** & **Problem Identify** & **Network Lifetime** & **Energy Wastages** & **Data Delivery** & **Data Aggregation** & **Methods** & **Limitations** \\ \hline \multirow{4}{*}{[82]} & Wildfire, earthquake, high chemical density and flood & Event driven & True or fault event & Residual energy & Forward node & Link reliability & Distributed event detection (DR) & Minimum event detection & Focus only on a specific environment \\ \cline{2-11}  & Monitoring an event of interest & Event driven & Overhead of mobile sink location & Shortest routing path & Transmitting and receiving data & Minimizes data & Reducing the delivery overhead of delay & Virtual based data dissemination & Data transmission link can be lost due to the presence of an disseman-obstacle in the sensing environment \\ \hline \multirow{4}{*}{[84]} & Grounded robots or vehicles & Event driven & Predefined trajectory & Mobile sink predefined & Fixed trajectory & Data Recovery & Number of hops & Do not handle a sensor-borne data & Do not handle a lifetime of network node data and energy consumption \\  & environment & & & & & & & \\ \hline \multirow{4}{*}{[85]} & Environmental monitoring & Event driven & Energy hole & Reducing the number of hops & Energy the sink run out of energy & - & Abnormal event & RP redundancy to save energy consumption \\ \hline \multirow{4}{*}{[86]} & Production efficiency of factories, monitoring and controlling individuals’ city data & Time & Spatial and temporal correlation & Faulty nodes & Whole sensor nodes & - & At the node level and the cluster & Matching-weighted and the cluster (EMWA), marginal and neighbor & Data sense collection is long due to this \\ \hline \multirow{4}{*}{[87]} & IoT data & Time & Outliers and and and energy & A load of network and energy & Dense sensor nodes, network & - & Cluster & Confine function, Random hash & Need data classification for accuracy \\  & community, & driven & & A data of network and network & Dense sensor nodes, network & - & Head & Aggregation, compression, and predictions & Do not tackle data collision and scheduling \\ \hline \multirow{4}{*}{[88]} & Temperature, humidity, light, and voltage & Time & Reliability and information & Data redundancy or similarities & Data transmission, sensor nodes, and a central node & - & Redundancy data & Aggregation, compression, and predictions & Do not tackle data collision and scheduling \\ \hline \multirow{4}{*}{[89]} & \multirow{4}{*}{Pit mining} & Time & Data aggregation of heterogeneous-neous & Data aggregation nodes, and a central node & Data transmission, sensor nodes, and a central node & - & Average, sum, minimum, and produce a & Deplete sensor batteries quite fast due to the high amount of data & Deplete sensor due to the high amount of data & Deplete sensor batteries quite fast due to the high amount of data & De the weight due to the high amount of data & Deplete to the high amount of data \\  & \multirow{4}{*}{[90]} & Home, industrial logistics, activation, health, manufacturing and military & Time & Data priority and frequent heterogeneous-neous & Data priority class for energy saving & & Class of traffic & Class of traffic & Still, data handling of data prioritization for the network layer of the WSN protocol & Still, data handling of data prioritization for the WSN protocol & Data prioritization for the WSN protocol & Still, data handling of data prioritization for the network layer of the WSN protocol & Still, data handling of data prioritization for the network layer of the WSN protocol & Still, data handling of data prioritization for the network layer of the network layer of the WSN protocol & Still, data prioritization for the network layer of the WSN protocol & Still, the network layer of the WSN protocol & Still, data function stack \\ \hline \multirow{4}{*}{[91]} & Temperature, light intensity, magnetism, seismic activity, sound, water level & Query driven and event & Data query dissemination and data gathering & Energy threshold changes & All the sensors & Data delivery rate and latency & - & Hybrid data dissemination & Do not consider QoS (Quality of Service) parameters and the connection & Do not handle a parameter and the mobility of some \\ \hline \multirow{4}{*}{[92]} & Coffee Arabica and Coffee Robust & Time & To detect time-driven or event-driven & Energy or event-driven or event-driven & Energy expected on cluster-free head & Data communication from sensor node to a base station & - & Each node level & Cluster-based data aggregation (CBDA) & Event-driven model accuracy true event information \\  & \multirow{4}{*}{[85]} & \multirow{4}{*}{[86]} & \multirow{4}{*}{[87]} & \multirow{4}{*}{[88]} & \multirow{4}{*}{[89]} & \multirow{4}{*}{[88]} & \multirow{4}{*}{[89]} & \multirow{4}{*}{[89]} & \multirow{4}{*}{[89]} & \multirow{4}{*}{[89]} & \multirow{4}{*}{[90]} & \multirow{4}{*}{[89]} \\  & Arabica and Coffee robust & Time & To detect time-driven or event-driven & Energy expected on cluster-free head & Data communication from sensor node to a base station & - & Each node level & Cluster-based data aggregation (CBDA) & Event-driven model accuracy true event information \\ \hline \hline \end{tabular}
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