## 2 Related Works
The data aggregation method is more suitable in periodic driven applications and it is ineffective in event driven based application like landmine detection. The clustering algorithm and Travelling Salesman Problem (TSP) based routing was presented in [35] to establish the path between sensor nodes and BS through UAV. In [36], LoRa communication technology was utilized to establish the communication between the UAV and on-ground sensors and collect the data from the agriculture field periodically. Policy-iteration based path planning algorithm was applied in routing formation which avoids the inter-unmanned surface vehicle collision [37]. A bi-level hybridization-based metaheuristic algorithm was deployed in [38] to find the tour planning and avoid the large blind searches in complex space. Neuro fuzzy based cluster formation and metaheuristic route formation was presented in [39], in which the remaining energy, distance to UAV and degree of UAV to cluster are considered in path planning. Voronoi diagram based path planning algorithm was used to linger the UAV's location with minimal computational effort to collect the data from the sensor node [40]. The water quality detection and sampling was performed using unmanned surface vehicle in which the particle swam optimization was used to find the feasible data collection path of seawolf USV [41]. In [42], the IoT-UAV grouping was executed using k-means clustering algorithm, in which the path contains optimal value of the completion time and energy consumption. The query based data collection scheme was presented in [43] to select the particular node based on the query and then send the UAV for collecting the sensed information. The comparison of existing methodology with the proposed TRT is given in Table 2.  
From the literature survey, it can be summarized as follows:  
1. Numerous routing protocols have been evolved in the past years to collect the data from the targeted area. However, the existing protocols are not suitable for all the applications in real time. For example, in tree topology based data collection, the number of nodes involved in each level is \(2^{n}\). The number of nodes participating in the sensing area grows (\(\sum_{i=0}^{n}2^{i}\)) as the depth of the tree increases in the existing tree topology-based data gathering. And for cluster topology, the number of node deployment depends on the transmission range of the sensor nodes. 2. The majority of research on WSNs focuses on periodic data collection, in which all sensor node nodes send data to the base station at regular intervals. 3. Most of the protocols utilise a large number of sensor nodes to collect data or detect an event in a specific area. 4. The majority of protocols are designed for a standard application and are intended to collect data from the sensing area and transmit it to the base station in a multi-hop fashion. In this paper, the T-based routing algorithm is specifically designed for collecting the data in landmine detection which utilizes a minimal number of nodes to cover large area and establish an effective communication using strip based network. It also extends the communication between the sensor node and BS by deploying the router nodes.