For bushfire prevention, in the process of agricultural and forestry monitoring, the project team considered common features such as the mobility, disconnection, and power capacity limitations of the sensor network. At the same time, it also carried out technical research and development on the following issues.
Communication capacity is limited. The communication bandwidth of sensors in a sensor network is narrow and often changes. The communication coverage range is only tens to hundreds of meters. Frequent disconnection of communication between sensors often leads to communication failures. Because sensor networks are more affected by high mountains, Landforms such as buildings and obstacles
As well as the impact of natural environments such as storms and lightning, sensors may leave the network for a long time and work offline. How to complete the processing and transmission of perceived information with high quality under the condition of limited communication capabilities is one of the challenges we face.
The power supply energy is limited. The sensor’s power supply energy is extremely limited. The sensors in the network often fail or are discarded due to the power supply energy. The power supply energy constraint is a serious problem that hinders the application of sensor networks. The needs of the network. Transmitting information by the sensor consumes more power than performing calculations. The energy required for the sensor to transmit 1 bit of information is sufficient to execute thousands of computing instructions. How to save energy during the network work and maximize the life cycle of the network is this project One of the issues that will be considered.
Limited computing power. Sensors in sensor networks have embedded processors and memories. These sensors have the computing power and can complete some information processing tasks. However, due to the limited capabilities and capacity of embedded processors and memories, the sensor’s computing Very limited capacity.
How to use a large number of sensors with limited computing capabilities for collaborative distributed information processing is a problem we need to face.
The number of sensors is large and the distribution range is wide. Sensor nodes in sensor networks are dense and huge in number, which may reach hundreds, tens of millions, or even more. In addition, sensor networks can be distributed in a wide geographical area. The number of sensors and the number of users It is also very large than usual.
The wide distribution makes network maintenance very difficult or unmaintainable. The software and hardware of the sensor network must be highly robust and fault-tolerant. This is to ensure accurate and reliable environmental monitoring, especially in tasks such as bushfire prevention. Important role.
The network is highly dynamic. The sensor network is highly dynamic. The three elements of the sensor, the sensing object, and the observer in the network may all have mobility, and often new nodes are added or existing nodes fail.
Therefore, the topology and structure of the network change dynamically, and the paths between the sensor, the sensing object, and the observer also change. The sensor network must be reconfigurable and self-adjusting.
Large-scale distributed triggers. Many sensor networks need to control the sensing object, such as temperature control. In this way, many sensors have a control device and control software. Call the control device and control software as triggers. Thousands of dynamic The management of triggers, especially the data flooding phenomenon triggered by the large-scale sudden situation evolution, will be one of our research topics.
The perceived data stream is huge. Each sensor in a sensor network usually produces large streaming data and has real-time nature. Each sensor has only limited computing resources and it is difficult to handle huge real-time data streams. Therefore, we also need to study powerful distributed data flow management, query, analysis, and mining methods.