# FL-MD3 QN-Based IoT Intelligent Access Algorithm for Smart Construction Sites
## 2 Problem Description  
In smart construction sites, IoT technology is widely used for environmental monitoring, equipment supervision, personnel management, safety alerts, and more. Deployed IoT sensors and devices include environmental sensors (monitoring air quality, noise levels, temperature, and humidity), video surveillance equipment (real-time site monitoring and accident prevention), smart access control systems (personnel management and site security), and GPS/RFID-based personnel positioning systems (tracking locations and improving efficiency). These enable intelligent, automated, and visual site management. Figure 1 shows a multi-modal, multi-user IoT application scenario where multiple sites share a single BS. The BS communicates wirelessly with IoT devices (video, sensors and voice devices) across sites. These devices collect data for transmission to edge servers. Edge servers process and analyze data to enable real-time decision making and enhance construction efficiency and safety. The multi-modal data generated by users include text, audio, images, and video. Each data type corresponds to distinct transmission rate and bandwidth requirements. Define as follows: Site set: \(k\) = {1,2,...,\(K\)}; User set: \(M_{k}\) = {1,2,...,\(M_{k}\)} for site k; Service modalities: N = {0 (text), 1 (audio), 2 (image), 3 (video)}; Time cycle: \(t\)\(\in\)\(T\); Access indicator: \(x_{k,m,n}(t)\)\(\in\){0,1}, \(\forall k\)\(\in\)\(K\), \(m\)\(\in\)\(M_{k}\), \(n\)\(\in\)\(N\), \(t\)\(\in\)\(T\), where \(x_{k,m,n}(t)\) = 1 indicates that user \(m\) in site \(k\) transmits modality \(n\) at time \(t\). Occupation time: \(t_{k,m,n}\) (time for user \(m\) transmitting modality \(n\)). A three-objective optimization model is formulated to:  
1. Maximize data transmission rate. \[\sum_{k\in K}\sum_{m\in M_{k}}\sum_{n\in N}R_{k,m,n}(t)\cdot x_{k,m,n}(t)\] (1) where \(R_{k,m,n}(t)\) is the rate for user \(m\) transmitting modality \(n\). (2) Minimize data transmission delay. \[\sum_{k,m,n}T_{k,m,n}^{total}(t)\cdot x_{k,m,n}(t) \tag{2}\]  
where \(T_{k,m,n}^{total}(t)\) is the end-to-end delay for modality \(n\). (3) Maximize reliability. \[\sum_{k,m,n}(1-BER_{k,m,n}(t))\cdot x_{k,m,n}(t) \tag{3}\]  
where \(BER_{k,m,n}(t)\) is the BER. Constraints:  
(1) Bandwidth constraint:  
\[\sum_{k,m,n}\frac{R_{k,m,n}(t)}{\eta_{k,m,n}(t)}\leq B_{total},\forall t \tag{4}\]  
where \(B_{total}\) is the total bandwidth of the BS. (2) Power constraint:  
\[\sum_{n}P_{k,m,n}^{tx}(t)\cdot x_{k,m,n}(t)\leq P_{k,m}^{max},\forall k,m,t \tag{5}\]  
where \(P_{k,m}^{max}\) is the maximum transmit power of user mm in site \(k\). (3) Processing capability constraint:  
\[\sum_{n}Q_{k,m,n}(t)\cdot x_{k,m,n}(t)\leq C_{k,m}^{max} \tag{6}\]  
where \(Q_{k,m,n}(t)\) is the data volume of modality \(n\), and \(C_{k,m}^{max}\) is the processing capability limit of the user device. (4) Total access time constraint:  
\[\sum_{k,m,n}t_{k,m,n}\leq T_{\max} \tag{7}\]  
where \(T_{\max}\) is the maximum total access time. (5) BER constraint:  
\[BER_{k,m,n}(t)\cdot x_{k,m,n}(t)\leq BER_{\max},\forall k,m,n \tag{8}\]  
where \(BER_{\max}\) is the maximum tolerable BER. (6) Transmission data association constraint:  
\[t_{k,m,n}=\frac{Q_{k,m,n}}{R_{k,m,n}}\cdot x_{k,m,n},\forall k,m,n \tag{9}\]The three-objective optimization problem is formulated as:  
\[\begin{split} opt.\left\{ \begin{array}{l}\max\sum\limits_{k\in K} \sum\limits_{m\in M_{k}}\sum\limits_{n\in N}R_{k,m,n}(t)\cdot x_{k,m,n}(t)\\ \min\sum\limits_{k,m,n}T^{total}_{k,m,n}(t)\cdot x_{k,m,n}(t)\\ \max\sum\limits_{k,m,n}(1-BER_{k,m,n}(t))\cdot x_{k,m,n}(t)\\ \end{array}