Wi-Fi Nodes Research Articles

Construction of a Wi-Fi System with a Tethered Balloon in a Mountainous Region for the Teleoperation of Vehicular Forestry Machines

In this study, a Wi-Fi system with a tethered balloon is proposed for the teleoperation of vehicular forestry machines. This system was developed to establish a Wi-Fi communication for stable teleoperation in a timber harvesting site. This system consisted of a helium balloon, Wi-Fi nodes, a measurement system, a global navigation satellite system (GNSS) antenna, and a wind speed sensor. The measurement system included a GNSS module, an inertial measurement unit (IMU), a data logger, and an altitude sensor. While the helium balloon with the Wi-Fi system was 60 m in the air, the received signal strength indicator (RSSI) was measured by moving a Wi-Fi receiver on the ground. Another GNSS set was also utilized to collect the latitude and longitude data from the Wi-Fi receiver as it traveled. The developed Wi-Fi system with a tethered balloon can create a Wi-Fi zone of up to 1.9 ha within an average wind speed range of 2.2 m/s. It is also capable of performing the teleoperation of vehicular forestry machines with a maximum latency of 185.7 ms.

Multitarget Device-Free Localization via Cross-Domain Wi-Fi RSS Training Data and Attentional Prior Fusion

Device-free localization (DFL) using easily-obtained Wi-Fi received signal strength (RSS) has wide real-world applications for not requiring people to carry trackable devices. However, accurate multitarget DFL remains challenging due to the unknown number of targets, multipath interference (MPI), especially between nearby targets, and limited real-world data. In this study, we pioneeringly propose a transformer-based learning method with Wi-Fi RSS as input, and an attentional prior fusion module, to simultaneously locate an unknown number of people at random positions. To overcome the multitarget data collection challenges, we contribute a large-scale cross-domain real-simulation-augmentation training dataset with one and two real-world nearby non-person objects at limited positions and up to five simulated and augmented randomly distributed targets. Experimental results demonstrate our method's improved accuracy, generalization ability, and robustness with fewer Wi-Fi nodes than previous methods.

Proportional Fairness for Long-Term Evolution-Licensed Assisted Access (LTE-LAA) with Wi-Fi Coexistence in Unlicensed Spectrum

Long-Term Evaluation-Licensed Assisted Access (LTE-LAA) has good potential for fair coexistence with Wi-Fi in an unlicensed spectrum. Though the LTE-LAA utilizes the same listen before-talk technique as the distributed coordination function in IEEE 802.11, it utilizes completely different parameters and transmission durations. For this reason, a fair coexistence between LTE-LAA and Wi-Fi leaves an open question on how the LTE-LAA network should choose its parameters. To tackle this issue, an analytical framework considering the effects of varying important parameters, which are the different initial back-off window sizes, the numbers of sensing durations, the maximum back-off stages, the number of retransmissions and the transmission opportunities for LTE-LAA and Wi-Fi nodes on their performances has been developed. The node and network airtime performances are evaluated by using the current standard parameters setting to see how this setting affects the node and network airtime performances. From there, optimal settings of the initial backoff window size and number of sensing durations are applied by using the obtained node airtime equation that is derived from the Markov renewal process and evaluated as functions of system parameters. The optimum initial backoff window size and number of sensing durations of LTE-LAA are evaluated and verified by the calculation and simulation using MATLAB software. The analysis shows that LTE-LAA maintained unfair coexistence with Wi-Fi by using the current standard parameter setting as its initial back off window size or sensing duration. But in contrast, using the optimum initial backoff window size and number of sensing durations of LTE-LAA shows that they can maintain proportional fairness. It is unconcealed that the initial backoff window size tuning of LTE-LAA carries a high possibility of achieving fairness because it needs less system data and achieves a higher exactness result.

Efficient Node Insertion Algorithm for Connectivity-Based Multipolling MAC Protocol in Wi-Fi Sensor Networks

Since low-power Wi-Fi sensors are connected to the Internet, effective radio spectrum use is crucial for developing an efficient Medium Access Control (MAC) protocol for Wi-Fi sensor networks. A connectivity-based multipolling mechanism was employed for Access Points to grant uplink transmission opportunities to Wi-Fi nodes with a reduced number of multipolling frame transmissions. The existing connectivity-based multipolling mechanism in IEEE 802.11 wireless LANs with many nodes may require excessive time to derive the optimal number of serially connected sequences due to the backtracking algorithm based on the Traveling Salesman Problem model. This limitation hinders the real-time implementation of the connectivity-based multipolling mechanism in Wi-Fi sensor networks. In this study, an efficient node insertion algorithm is proposed, by which the number of derived serially connected multipolling sequences that cover nodes in Wi-Fi sensor networks converges to only one as the number of Wi-Fi sensors increases in Wi-Fi sensor networks. As verified by simulation experiments for Wi-Fi sensor networks, the proposed node insertion algorithm produces a near-optimal number of multipolling sequences that cover the nodes in Wi-Fi sensor networks. This study proposes a node insertion algorithm for the real-time implementation of the connectivity-based multipolling mechanism in MAC protocol for Wi-Fi sensor networks.

2.5 GHz to 3.5 GHz fractal metasurface microstrip antenna design for high bandwidth wireless applications

In this paper, the microstrip slot antenna is designed for a wireless application with fractal structure having 2.5 - 3.5 GHz coverage and 30% bandwidth. The circular slot antenna with seven triangular slots is considered and six single rings are added to the antenna. As a last step, the enhancement of the matching is produced by a disk located the central part of the slot. The fractal model improves the bandwidth, modifies the antenna matching and controls the current distribution in such a way that it is used in the S (short) band in our case for WiMAX technology, which allows wireless transmission of voice, data and video in areas of up to 48 km radius. It was projected as a wireless alternative to ADSL and cable broadband access, and a way to connect Wi-Fi nodes in a metropolitan area network. The antenna gain is about 19.37 dB with a compact size of 60 × 60 mm2. The metasurface structure helps us to improve the bandwidth. The antenna was simulated with Ansoft Designer V.3.5. The antenna is designed in FR4 as the most suitable material as well as being low cost and accessible. It is proved that the fractal shape is used to improve the bandwidth. The result of combining the metasurface with the antenna can be considered to improve the bandwidth

A Review of RFID Sensors, the New Frontier of Internet of Things.

A review of technological solutions for RFID sensing and their current or envisioned applications is presented. The fundamentals of the wireless sensing technology are summarized in the first part of the work, and the benefits of adopting RFID sensors for replacing standard sensor-equipped Wi-Fi nodes are discussed. Emphasis is put on the absence of batteries and the lower cost of RFID sensors with respect to other sensor solutions available on the market. RFID sensors are critically compared by separating them into chipped and chipless configurations. Both categories are further analyzed with reference to their working mechanism (electronic, electromagnetic, and acoustic). RFID sensing through chip-equipped tags is now a mature technological solution, which is continuously increasing its presence on the market and in several applicative scenarios. On the other hand, chipless RFID sensing represents a relatively new concept, which could become a disruptive solution in the market, but further research in this field is necessary for customizing its employment in specific scenarios. The benefits and limitations of several tag configurations are shown and discussed. A summary of the most suitable applicative scenarios for RFID sensors are finally illustrated. Finally, a look at some sensing solutions available on the market are described and compared.

Deployment Strategies of Soil Monitoring WSN for Precision Agriculture Irrigation Scheduling in Rural Areas.

Deploying wireless sensor networks (WSN) in rural environments such as agricultural fields may present some challenges that affect the communication between the nodes due to the vegetation. These challenges must be addressed when implementing precision agriculture (PA) systems that monitor the fields and estimate irrigation requirements with the gathered data. In this paper, different WSN deployment configurations for a soil monitoring PA system are studied to identify the effects of the rural environment on the signal and to identify the key aspects to consider when designing a PA wireless network. The PA system is described, providing the architecture, the node design, and the algorithm that determines the irrigation requirements. The testbed includes different types of vegetation and on-ground, near-ground, and above-ground ESP32 Wi-Fi node placements. The results of the testbed show high variability in densely vegetated areas. These results are analyzed to determine the theoretical maximum coverage for acceptable signal quality for each of the studied configurations. The best coverage was obtained for the near-ground deployment. Lastly, the aspects of the rural environment and the deployment that affect the signal such as node height, crop type, foliage density, or the form of irrigation are discussed.

Low‐Cost and Long‐Range Node‐Assisted WiFi Backscatter Communication for 5G‐Enabled IoT Networks

The fifth‐generation‐enabled Internet of Things (5G‐enabled IoT) has been considered as a key enabler for the automation of almost all industries. In 5G‐enabled IoT, resource‐limited passive devices are expected to join the IoT using the WiFi backscatter communication (WiFi‐BSC) technology. However, WiFi‐BSC deployment is currently limited due to high equipment cost and short transmission range. To address these two drawbacks, in this paper, we propose a low‐cost and long‐range node‐assisted WiFi backscatter communication scheme. In our scheme, a WiFi node can receive backscatter signals using two cheap regular half‐duplex antennas (instead of using expensive full‐duplex technique or collaborating with multiple other nodes), thereby reducing the equipment cost. Besides, WiFi nodes can help relay backscatter signals to remote 5G infrastructure, greatly extending the backscatter’s transmission range. We then develop a theoretical model to analyze the throughput of WiFi‐BSC. Extensive simulations verify the effectiveness of our scheme and the accuracy of our model.

Listen Before Receive (LBR) Assisted Network Access in LAA and WiFi Heterogeneous Networks

The Listen-Before-Talk (LBT) is the main procedure for Licensed Assisted Access (LAA) to accomplish fair and friendly coexistence with other operators or technologies operating over unlicensed spectrum. However, in LBT, the lack of coordination with other existing systems brings challenges in sustaining performance in the coexistence of LAA and WiFi networks. Specifically, the hidden node problem (HNP) and exposed node problem (ENP) cannot be effectively handled when both LAA and WiFi nodes attempt to access the unlicensed spectrum at the same time. Thus, transmission failure might occur and the network performance would be degraded. In order to mitigate the influences caused by HNP and ENP, based on LBT, we firstly analyze HNP and ENP by means of mathematical approach. The analytical results surprisingly reveal that the hidden node and exposed node probabilities are as high as 41% and 39.33%, respectively. Then, a Give And p-persistent Take (GAT) mechanism with the Listen-Before-Receive (LBR) procedure, namely LBR-GAT, is proposed to cope with LBT to reduce the collision caused by HNP as well as to retrieve the bandwidth sacrificed by the ENP. With LBR-GAT, the LAA sender conditionally gives up or takes back transmission opportunities, and thus the unlicensed spectrum could be efficiently shared between LAA and WiFi. Evaluation results show that the proposed LBR-GAT could conditionally obtain better network performance comparing to legacy LBT.

ERFR-CTC: Exploiting Residual Frequency Resources in Physical-Level Cross-Technology Communication

In Internet of Things (IoT), physical-level cross-technology communication (CTC) enables IoT gateways to communicate with heterogeneous nodes economically. However, because of bandwidth asymmetry between heterogeneous technologies, many residual frequency resources are often not fully utilized. Without modification on hardware, in this article, we consider the coexistence of ultralow power (ULP) and WiFi nodes, and propose ERFR-CTC that enables an IoT gateway to fully exploit residual frequency resources without adding additional cost. With ERFR-CTC, the gateway can simultaneously communicate with ULP and WiFi nodes only via a single WiFi network interface card (NIC), which is not only economic but also very efficient. In particular, ERFR-CTC enables ULP nodes to correctly demodulate ULP signals without being interfered by WiFi signals. We then develop theoretical models to quantify available residual frequency resources and analyze the system throughput. Finally, extensive simulations verify that our model is very accurate and show that ERFR-CTC can increase the system throughput by up to 51.4%.

Neighbor Discovery Based on Cross-Technology Communication for Mobile Applications

Neighbor discovery is essential for mobile devices to find each other before communications. Traditional discovery protocols are constrained by the in-technology communication paradigm. Cross-Technology Communications enable ZigBee nodes to be coordinated by a WiFi node without any hardware changes or gateway equipment, which sheds the light on more efficient neighbor discovery schemes. In this work, we introduce a new direction for neighbor discovery based on Cross-Technology Communication technique and propose a physical-layer technique called NewBee. NewBee takes the advantages of coordinations from a WiFi node to assist ZigBee nodes for neighbor discovery. A simple yet effective Countdown Mechanism is employed so that ZigBee nodes are coordinately waked up according to the beacons in the Countdown Mechanism. We give a rigorous analysis on NewBee and the worst-case discovery latency is significantly reduced from the traditional $O(n^2)$ to $O(n)$ , where $n$ indicates the reciprocal of node's duty-cycle. The experimental results show that NewBee only needs 11%, 10%, 2.5%, 2.4% and 4.4% percent of discovery time compared with the state-of-the-art BlindDate, SearchLight, Disco, Quorum, and Birthday protocols with 5% nodes’ duty-cycle, respectively.

Reinforcement Learning for Efficient and Fair Coexistence Between LTE-LAA and Wi-Fi

Long-Term Evolution (LTE) over unlicensed spectrum extends LTE technology to the spacious unlicensed spectrum with readily available bandwidth. The provided capacity surge makes it one of the most high-profile technologies to meet the explosive growth of mobile traffic demand. Among its different variants, Licensed Assisted Access (LAA) is considered as a promising global solution attributed to its mandatory listen-before-talk (LBT) procedure. Nevertheless, although LBT effectively maintains transmission fairness between LTE and other unlicensed systems (e.g., Wi-Fi), the current LAA protocol specified in 3GPP Release 13 is far from perfect to achieve harmony coexistence. To this end, in this paper, we first develop an analytical model to evaluate the throughput performance of Category 4 (Cat 4) algorithm agreed in 3GPP release 13. Subject to the system fairness constraint, the aggregate throughput of LTE-LAA and Wi-Fi networks is maximized based on a semi branch and bound algorithm. To make the complex optimization tractable, reinforcement learning techniques are introduced to intelligently tune the contention window size for both LTE-LAA and Wi-Fi nodes. Specifically, a cooperative learning algorithm is developed assuming that the information between different systems is exchangeable. A non-cooperative version is subsequently developed to remove the previous assumption for better practicability. Extensive simulations are conducted to demonstrate the performance of the proposed learning algorithms in contrast to the analytical upper bound under various conditions. It is shown that both proposed learning algorithms can significantly improve the total throughput performance while satisfying the fairness constraints. Particularly, the proposed cooperative learning algorithm can closely approach the analytical bound.

Achieving Proportional Fairness for LTE-LAA and Wi-Fi Coexistence in Unlicensed Spectrum

LTE Licensed Assisted Access (LTE-LAA) is a promising solution for harmonious coexistence with WiFi in unlicensed spectrum. Although LTE-LAA employs a listen-before-talk approach similar to the distributed coordination function in IEEE 802.11, it uses different parameters and varying transmission durations. As a result, achieving fair coexistence between LTE-LAA and WiFi (by any definition) remains an open question, which in a pragmatic framework, devolves to: how LTE-LAA should select its parameters. To address this issue, a multi-group model is proposed for LTE-LAA and WiFi coexistence, as a function of respective initial backoff window sizes, sensing durations, maximum backoff stages, retry limits and transmission opportunities. The network steady-state point in saturated conditions is obtained, based on which the node airtime and total network airtime are derived as functions of system parameters of LTE-LAA and WiFi networks. The analysis shows that LTE-LAA can maintain proportional fairness with WiFi by either tuning its initial backoff window size or sensing duration. In particular, the optimal initial backoff window size and number of sensing slots of LTE-LAA are both derived and verified by simulation. The significance of our analysis is two-fold: a) it exposes the result that the current standard-proposed parameter settings will not generically achieve fairness and thereafter b) suggests optimal settings whereby LTE-LAA and WiFi nodes can achieve equal per-node airtime. It is further revealed that the initial backoff window size tuning of LTE-LAA could be a preferable option for achieving fairness between LTE-LAA and WiFi in practical scenarios as it requires less system information and achieves better precision.

Improving Network Trust using Blockchain Based Communication Links

Wireless networks enable wireless-nodes to develop and broadcast messages in an attempt to reinforce congestion protection and performance. Meanwhile, due to distrust environments, it’s mile tough for the wireless-nodes to assess in reliability of the acquired messages. In this work, we advise the decentralized control machine in Wireless networks situated on the blockchain techniques. During this machine, wireless-nodes must be verifying obtained messages from the neighboring Wi-Fi nodes by using Bayesian Inference Model. On the idea of this validation outcome, Wi-Fi node is going to be generated the rating for every message source of wireless-node. With this ranking uploaded from Wi-Fi nodes, Roadside Units are often calculated the trust cost offsets of worried wireless nodes, p.C. This statistic right into the block. Then, to every of the Roadside Unit are going to be attempt for adding their “blocks” to be consider block chain that's maintain with aid of all Roadside Units. Make the utilization of the joint Proof-of-Work and Proof-of-Stake consensus the system, extra overall fee of the offset (stake) is within a block, more easy the Roadside Unit are often located the nonce for their hash feature (evidence-of-paintings).During this manner, all the Roadside Unit collaboratively preserve an up to the date, dependable, and steady believe blockchain. Clone results can display that the proposed gadget be powerful also a possible in accumulating, computing, and storing agrees with values in Wireless networks.

Improved Fingerprinting based Indoor Positioning System with Hybrid Sensor Fusion to Overcome the Practical Hinderance

Indoor tracking has evolved with various methods, and the most popularly used method is using signal strength measuring techniques like trilateration, triangulation, and fingerprinting, etc. Out of all the popular techniques, the Wi-Fi fingerprinting method to localize users has been attracting much attention because it doesn’t require any line- of- sight. The offline phase takes into account of LOS or any permanent hindrances to the access point radio signal during the recording of the Fingerprinting dataset. In the online phase by comparing the RSSI values and using KNN /WKNN can detect the location of one’s position in indoor where the GPS signals can’t be reached. The offline phase requires much more effort to capture RSSI values, and any change in the environment or location of the Wi-Fi access point requires all the calibration in offline need to repeat, which is tedious. Even a temporary moving block like humans/doors/new construction will affect the accuracy of positioning in the online phase. The proposed algorithm detects the affected Wi-Fi nodes hindered by blocks and eliminates those during the online comparison phase, so then improves the accuracy. This algorithm also is useful in identifying the block is permanent or temporary to optimize the retake of the offline phase. The experimental result shows that the proposed hybrid sensor fused method improves the position estimation over the Fingerprinting method.

An SDR implementation of WiFi receiver for mitigating multiple co-channel ZigBee interferers

Machine-to-machine (M2M) communication is one of the vertical sectors that will benefit from 5G communication systems, but today, these systems are still dominated by technologies such as ZigBee and WiFi. An M2M scenario will experience dense deployment of ZigBee and WiFi nodes in order to route the data from one end to the other. In the 2.4 GHz industrial, scientific, and medical (ISM) band, both of the technologies perform co-channel overlapped operation and hence face severe cross technology co-channel interference (CCI). In contrast to cellular systems, which solve the CCI by centralized coordination through the base station, addressing CCI in the ISM band is non-trivial due to heterogeneous wireless technologies and the lack of centralized coordination. In this work, we first present interference mitigating receiver architectures for OFDM-based WiFi using single and multiple antennas. Our single antenna work is based on the localized estimation of excess noise caused by single and multiple co-channel narrowband interferers and scaling the log-likelihood ratios (LLRs) of the affected WiFi subcarriers. The simulation shows our method achieves a significant gain in SNR compared to the conventional method for a given packet error rate (PER) criterion. Next, we discuss maximal ratio combiner with LLR scaling (MLSC), which is a multi-antenna extension to our previous work. The simulation shows MLSC achieves diversity gain apart from the gain in SNR. Further, we propose soft-bit maximal ratio combiner with LLR scaling (SB-MLSC). SB-MLSC is an easy to implement version of MLSC. However, diversity combining in SB-MLSC is performed by combining the LLRs. Nonetheless, simulations show equivalence in performance by SB-MLSC and MLSC. Finally, as a significant part of this work, we implemented all our methods using a software-defined radio (SDR) and performed over-the-air (OTA) testing in the 2.4-GHz ISM band using standard WiFi and ZigBee frames. Results of OTA tests fall in complete agreement with our simulations indicating the practical applicability of our methods. Our methods apply to all the standards and related radio transmission techniques which are based on OFDM and face narrowband co-channel interference. Additionally, since our work focuses only on receiver side modifications, they can be integrated with the existing infrastructure with minimal modifications.

Indoor Multifloor Localization Method Based on WiFi Fingerprints and LDA

Indoor localization has elicited increasing attention because it has been widely used in indoor location-based services. At present, many complex scenarios for indoor localization require position estimation not only in single-floor environments but also in multifloor ones. However, existing works exhibit certain limitations in solving the problems that involve high computational complexity and floor localization accuracy. In this paper, a multifloor identification system based on WiFi fingerprint database is designed to address these issues. This floor identification system is divided into offline and online phases. In the offline phase, a localization fingerprint database is built based on WiFi nodes and a multifloor identification model is proposed based on linear discriminant analysis (LDA), called MA_LDA. In the online phase, the final floor number is determined, and the trained model is combined with the majority voting mechanism. After determining the floor number, an algorithm based on the k-nearest neighbor (KNN), called LL_KNN, is proposed to obtain the location information of a target on the floor. Real experiment results show that our system can identify the floor number by using only a little WiFi node fingerprint information rather than all the nodes to reduce the computational complexity. It works efficiently and achieves high fault-tolerance performance compared with existing approaches in locating targets in a multifloor environment.

A novel dynamic localisation system for indoor and outdoor tracking

ABSTRACTHybrid indoor and outdoor localisation system has generated substantial interest from researchers due to its potential use in many fields. Many research papers on hybrid localisation were focused on localisation accuracy and computation time instead of the process for seamless switching during the subject’s indoor-outdoor movement. Seamless and stable switching can improve the usability and practicality of a system in an ever-changing scenario. This paper presents a hybrid localisation system that can adapt to the changes in the environment. Two hybrid systems – Enhanced Fusion Hybrid (EFH) and Enhanced Unified Hybrid (EUH), and novel signal selection and switching algorithms suitable for dynamic environment where signal fluctuations and transient condition frequently occur, i.e. the Clean Radio Signal Label (CRSL) classification algorithm and the Adaptive Signal Thresholding (AST) algorithm are proposed. From the experimental results of EFH and EUH methods, the GPS and Wi-Fi combination produces the best results as compared to the combinations of GPS and GSM or GSM and Wi-Fi. The accuracy of estimates was improved to 2.0 m to 5.0 m. Further work shown that an accuracy of 2.0 m or less could be achieved with an increase in Wi-Fi nodes from three to four for the system.

Null-While-Talk: Interference nulling for improved inter-technology coexistence in LTE-U and WiFi networks

A recent proposal known as unlicensed LTE offers cost-effective capacity extension to the cellular network operators in which LTE operators bundle the unlicensed spectrum in 5GHz UNII bands with their licensed spectrum via carrier aggregation. But, unlicensed spectrum requires coexistence among the networks operating in the same spectrum, e.g., IEEE 802.11 (WiFi) networks at 5GHz. While WiFi implements Listen-Before-Talk (LBT) and is therefore coexistence-friendly, LTE-Unlicensed (LTE-U) lacks such capability as it is not designed with shared spectrum access in mind. Hence, LTE has a potential to seriously harm WiFi. Prior works suggest forcing LTE-U to separate its transmission in either frequency, time, or space, and without directly collaborating with the WiFi networks. Contrary to these schemes, we introduce an explicit cooperation between neighboring LTE-U and WiFi networks. We propose Null-While-Talk(NWT) which suggests that LTE-U BSs employ MIMO signal processing to create coexistence gaps in space domain in addition to the time domain gaps by means of cross-technology interference nulling towards WiFi nodes in the interference range. In return, LTE-U can increase its own airtime utilization while trading off slightly its gain from MIMO. First, we present simulation results indicating that such cooperation offers benefits to both networks, WiFi and LTE-U, in terms of improved throughput and decreased channel access delay. Moreover, we present Xzero which implements NWT in a practical setting where the LTE-U BS lacks channel state and location information about the WiFi stations to be nulled. Xzero overcomes this challenge by performing an intelligent null search guided by constant feedback from the WiFi node on the null directions being tested. Our Xzero prototype implemented on SDR and COTS WiFi hardware shows the feasibility of our proposal.

Internet of Energy: A Design to Manage Energy Consumption for Off-Grid Building

Abstract: This article offers an Internet of thing (IoT) based energy management system, that provide an automation concept and completely control the consumed energy by observing the delivered power from a limited and/or unreliable power sources. An example for such sources are photovoltaic and wind renewable energy where the supplied power depends on the weather conditions which make it fluctuated and unreliable. The proposed system offers a complete solution to reduce the consumed power based on the available power with less affecting on the quality of life. This article presents a cloud computing master unit that communicates with all the building devices via WIFI network nodes. These nodes are responsible for calculating the consumed energy by each connected device and deliver this information to the cloud. The system enables the user to schedule the devices’ levels of priority in a list, priority list. The master controller unit calculates the available power based on instantaneous supplied power from the source, stored energy, weather prediction, and priority list, then make a decision to keep all the devices powered on or shut down some of them for a while according to the list.This article presents an Internet of thing (IoT) system, which offers a complete energy consumption, monitoring and control. There is a master controller which is a website built with Ajax software to communicate with all the building devices (via a wireless router) which connected to Wi-Fi nodes (ESP8266 nodes) to calculate the consumed energy from each device and compare it with the fluctuated produced energy. The system is designed to keep the consumed energy, lower than the produced energy. This can be achieved by making the user take the decision and divides the building devices into three different priorities (High, Medium and Low). The presented system follows a strategy to reduce the load according to the available power and the device priority. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License .