# Opportunities and Challenges for Error Control Schemes for Wireless Sensor Networks: A Review
## 6 Future Research Challenges and Opportunities  
WSN has wide ranging applications including military, monitoring of health and environment, industry and home automation. Those applications require different levels of reliability and data rate, and it also requires covering varying communication distance depending on the applications.Therefore, one static solution does not fit for all applications. Hence, the future ECS should be dynamic and adaptive to handle a variety of WSN nodes, reliability requirements and communication channels. Thus, the researchers should focus on integration of software-defined radio concept [102; 103; 104] in the context of adaptive ECS design and implementation in WSN. The efficient design and implementation of ECS in WSN should exploit node constraints and channels. The exploitation of node constraints and channels is possible in SHAS WSN structures. Those structures practically exist at home and industry automation, building monitoring and Wireless Body Area Network (WBAN), where the distance between nodes is smaller and the base station node is not energy and computationally constrained. Therefore, the researchers need to do more work on energy efficiency analysis and ECS design using capacity approaching codes (such as LDPC, RA and turbo code) in SHAS structure. Hence, the following research areas need to be examined further in order to design efficient ECS. This can be achieved by introducing dynamic and adaptive features in WSN. * Dynamic and adaptive ECS design based on the software-defined radio in order to support variety of nodes, channels, and QoS requirements in WSN. * Scholarly work addressing the use of power adaptive techniques at the transmitter in ECS design in WSN is not found. We advise researchers to investigate the use of power adaptive technique in ECS design. * Our review on adaptive techniques used in ECS design for WSN in Section 5.2 found that many techniques have been analysed in terms of communication link performance. The adaptive process demands additional tasks during implementation. However, the impact of using those additional tasks in energy consumption is lacking. * As we discussed in Section 3.1, WSN is implemented in an unlicensed frequency range, and there is a significant interference due to other wireless networks including WSN, WLAN and WBAN. Therefore, the efficiency of ECS for WSN in practical situations depends on interference from other systems. Further research is expected to analyse the efficiency of ECS for WSN in practical and real-life settings with interference. * Our review on the energy consumption model in Section 4 indicates that most of the research work conducted was based on old hardware. However, there is new hardware available in the market and this new hardware will be mostly used in the future. Hence, more research work is recommended on energy consumption models in order to keep pace with new developments in sensor nodes. * To design and implement ECS for WSN, researchers need to do more work on network modelling to incorporate practical WSN which extract several parameters such as wireless channel, node feature, reliability and data rate. * Another challenge is to verify ECS design for WSN in practical settings. Most of the previous work is completed in isolated situations or using theoretical channels. Therefore, the creation of experimental settings that resemble various WSN application scenarios is a challenge but requires some further work. Furthermore, Table 5 illustrates the summary of key issues, opportunities and challenges in ECS design for WSN.