## 6 Future Research Directions
### Technology
The power consumption of DAS increases following the sophistication of electronic devices and the medium of data transmission. A LoRa technology consumes less power than Wi-Fi, NB-IoT, and ZigBee. NB-IoT consumes very high power compared to Wi-Fi, ZigBee, and LoRa. However, the bit rate of LoRa is limited compared to NB-IoT, ZigBee, and Wi-Fi technologies. Moreover,DAS size affects the power consumption level because increasing the number of layouts and connection cables increases the power consumption level. The power Standalone criterion represents DAS's capability to be powered using solar panels or thermoelectricity sources. DAS latency criterion represents the entire latency of the DAS system to acquire real-time data from the field of experiment. DAS latency is also related to the technology of data transmission from the experimental site, the number of sensors connected to the MCU board, the number of MCU boards, and cloud-based or gateway-based IoT architecture. Also, using different technologies in one architecture increases the DAS latency, i.e., if ZigBee, NB-IoT, and UAV are in one IoT structure, hence the DAS poses a considerable amount of latency. Hence, the complexity of DAS is related somehow to the DAS latency. Also, the information size of collected raw data increases DAS complexity because additional time is required to process the received amount of data. Information diversity also indicates that DAS needs varied processing/analysis tools to produce raw data. It can be seen from Table 1 that different electronic boards have been proposed in the literature. The off-the-shelf components (Arduino, Raspberry Pi) were the most used ones in experimental studies. A few other boards from Intel and other manufactured companies are also used. However, these boards are required to be programmed before usage, not like off-the-shelf components. Also, the technology most widely adopted in communication is Wi-Fi, which connects the MCU board to the internet via a wireless connection. This, in turn, needs to be supplied with a power resource and it's a problem for remote locations. LoRa and ZigBee communication technologies are also used with low power consumption. However, Zigbee is used for short-range communication (10-100) m while LoRa is used for WAN to cover (1-5) km in the city and 15 km in the open area. It can be pointed out from this Table that developers did not use Nb-IoT technology in their implementation. This raises a concern about its suitability for IoT applications as it might be related to power consumption, cost, and DAS complexity since this technology requires special operation and maintenance. Wi-Fi technology is also used in connecting the main controller board to the internet gateway. However, this technology consumes a lot of power and only works for a short range despite its availability and cost efficiency. Hence, this technology is not suitable to be deployed in a long-range or wide area. For the sensor part, the PH sensor is the most used in the literature, followed by turbidity, conductivity, temperature, and O\({}_{2}\) sensors. The chemical characteristics sensors are less used in real-time experiments like Nitrite, Fluoride, Chloride, and Sodium sensors. Some IoT solutions proposed in the literature focus on constructing a cost-efficient architecture, neglecting the reliability and scalability of these architectures. I.e., it's not feasible to connect 15 sensors to a single off-the-shelf MCU board since the data collected needs larger memory to preprocess the collected fetched raw data. Moreover, providing power to the off-the-shelf boards is challenging in its nature since these boards are limited in their hardware and software capabilities. Moreover, no solution offered a data fusion technique to provide a reliable dataset.