# Green IoT: A Review and Future Research Directions
## 5 Energy-Efficient and Eco-Sustainable Wireless Sensor Networks
### Radio Optimization Techniques  
The radio unit is the main reason for the battery drain on sensor nodes. The energy consumption of the radio unit can be attributed to two factors: (i) power required for the circuit itself to function and (ii) power needed to transmit the signal. It is well-known that for shorter distances, the power required for the circuit itself to function is greater than the power needed to transmit the signal. However, for longer distances, the power required for the transmitted signal becomes the dominant factor in energy consumption. There have been several studies that have explored ways to improve energy efficiency by dynamically adjusting the transmission power level [45; 46]. The authors in [47] proposed an energy  
Figure 6: Classification of energy-efficient techniques for WSNs.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Wireless Technology** & **Healthcare** & **Smart Cities** & **Smart Building** & **Automotive** & **Industry** & **Local Network (M2M)** \\ \hline Bluetooth (BLE) & very high & low & low & very low & very high & medium \\ LR-WPAN & medium & high & low & very low & low & high \\ LoRa & low & high & high & high & high & high \\ WiFi & low & high & medium & medium & low & high \\ WiMAX & low & very high & high & high & very high & high \\ Mobile communication & low & high & high & high & medium & very low \\ \hline \hline \end{tabular}
\end{table}
Table 3: The suitability of various wireless technologies for IoT applications [42; 43].  
saving cooperative topology that allows nodes with higher remaining energy to increase their transmission power, which allows other nodes to decrease their transmission power. This can reduce interference and improve connectivity, but may also potentially increase the delay as more hops may be needed to forward a packet. Cooperative communications among neighboring sensor nodes can address the delay problem by creating a virtual multiple-antenna environment, providing spatial diversity and enabling retransmission of data. Cooperative communications among neighboring sensor nodes can improve the quality of the received signal by reducing the effects of multi-path fading and shadowing, extending the communication range among sensor nodes, and providing better energy savings and smaller end-to-end delays over certain transmission range distances. This has been reported in studies such as [PERSON] et al. [48] and [PERSON] [49], who have compared the energy consumption of single input single output and virtual multiple-antenna (multiple input and multiple output) systems and found that the virtual multiple-antenna system offers better energy savings and smaller end-to-end delays under certain conditions. On the other hand, [PERSON] et al. [50] have studied the relationship between energy consumption, transmission time, and bit error rate. The results showed that optimizing the transmission time can minimize the energy consumption needed to meet a given bit error rate and delay requirement. In addition, the authors in [51] conducted a comparison of the energy efficiency of three different modulation schemes to determine the optimal modulation scheme that achieves the lowest energy consumption at various distances between sensor nodes.