Accurate indoor positioning system based on modify nearest point technique

Wireless fidelity (Wi-Fi) is common technology for indoor environments that use to estimate required distances, to be used for indoor localization. Due to multiple source of noise and interference with other signal, the receive signal strength (RSS) measurements unstable. The impression about targets environments should be available to estimate accurate targets location. The Wi-Fi fingerprint technique is widely implemented to build database matching with real data, but the challenges are the way of collect accurate data to be the reference and the impact of different environments on signals measurements. In this paper, optimum system proposed based on modify nearest point (MNP). To implement the proposal, 78 points measured to be the reference points recorded in each environment around the targets. Also, the case study building is separated to 7 areas, where the segmentation of environments leads to ability of dynamic parameters assignments. Moreover, database based on optimum data collected at each time using 63 samples in each point and the average will be final measurements. Then, the nearest point into specific environment has been determined by compared with at least four points. The results show that the errors of indoor localization were less than (0.102 m).

An autonomous navigational system using GPS and computer vision for futuristic road traffic

Navigational service is one of the most essential dependency towards any transport system and at present, there are various revolutionary approaches that has contributed towards its improvement. This paper has reviewed the global positioning system (GPS) and computer vision based navigational system and found that there is a large gap between the actual demand of navigation and what currently exists. Therefore, the proposed study discusses about a novel framework of an autonomous navigation system that uses GPS as well as computer vision considering the case study of futuristic road traffic system. An analytical model is built up where the geo-referenced data from GPS is integrated with the signals captured from the visual sensors are considered to implement this concept. The simulated outcome of the study shows that proposed study offers enhanced accuracy as well as faster processing in contrast to existing approaches.

Dynamic Selection Techniques for Detecting GPS Spoofing Attacks on UAVs

Unmanned aerial vehicles are prone to several cyber-attacks, including Global Positioning System spoofing. Several techniques have been proposed for detecting such attacks. However, the recurrence and frequent Global Positioning System spoofing incidents show a need for effective security solutions to protect unmanned aerial vehicles. In this paper, we propose two dynamic selection techniques, Metric Optimized Dynamic selector and Weighted Metric Optimized Dynamic selector, which identify the most effective classifier for the detection of such attacks. We develop a one-stage ensemble feature selection method to identify and discard the correlated and low importance features from the dataset. We implement the proposed techniques using ten machine-learning models and compare their performance in terms of four evaluation metrics: accuracy, probability of detection, probability of false alarm, probability of misdetection, and processing time. The proposed techniques dynamically choose the classifier with the best results for detecting attacks. The results indicate that the proposed dynamic techniques outperform the existing ensemble models with an accuracy of 99.6%, a probability of detection of 98.9%, a probability of false alarm of 1.56%, a probability of misdetection of 1.09%, and a processing time of 1.24 s.

Design Space Exploration of a Multi-Model AI-Based Indoor Localization System

In this paper, we present the results of a performance evaluation and optimization process of an indoor positioning system (IPS) designed to operate on portable as well as miniaturized embedded systems. The proposed method uses the Received Signal Strength Indicator (RSSI) values from multiple Bluetooth Low-Energy (BLE) beacons scattered around interior spaces. The beacon signals were received from the user devices and processed through an RSSI filter and a group of machine learning (ML) models, in an arrangement of one model per detected node. Finally, a multilateration problem was solved using as an input the inferred distances from the advertising nodes and returning the final position approximation. In this work, we first presented the evaluation of different ML models for inferring the distance between the devices and the installed beacons by applying different optimization algorithms. Then, we presented model reduction methods to implement the optimized algorithm on the embedded system by appropriately adapting it to its constraint resources and compared the results, demonstrating the efficiency of the proposed method.

Roles of Geospatial Technologies in Hydrographic Practice

Any seafarer or mariner that uses the sea knows that navigation without correct charts is impossible and hazardous because nautical charts are the most essential and indispensable tools for vessels to sail safely at sea. For vessels to safely sail at sea, the seas and the oceans ought to be charted and this falls within the domain of hydrography. However, the seas cannot be charted effectively in the absence of the deployment of human resources and adequate tools like satellite and aerial imagery, survey boats and other equipment that will facilitate the hydrographic operations. The acquisition of data and information about the sea depths, nature of sea bed, waterways, navigational hazards and navigational objects among others, basically falls within the sphere of hydrography which is primarily known as survey at sea. The paper offers a review of geospatial technologies in hydrographic practice for enhanced safety of navigation at sea. The review is important to both the mariners, shipping industry and the government in order to explore the potentials provided by Geographic Information System, Remote Sensing, cloud GIS, big data GIS and Global Positioning System to enhance the practice of hydrography. The data and materials used for the review were obtained from literature in the internet and other published works. The paper looked at hydrography as a profession, roles of geospatial technologies in hydrographic practice, benefits of hydrography to national development and finally, the weaknesses of geospatial technologies in hydrographic practice were equally examined.

The content and load of preseason field-based training in a championship-winning professional rugby league team: A case study

This study reports on the content and periodisation of the preseason field-based training for a professional rugby league team. Thirty professional male rugby league players (26 ± 5 years, 180.9 ± 6.5 cm, 94 ± 9 kg) completed an 8-week preseason. Global positioning system devices and heart rate were used to monitor physical and physiological responses of different field-based training components (speed, conditioning, rugby skill and game-based training). Rugby skill training contributed the most to the total distance covered, conditioning was the greatest contributor to high-speed running (>15 km/h) and game-based training provided the greatest high metabolic distance (>20 W/kg) and overall external load. Game-based training provided the greatest time with heart rate ≥80% estimated maximum. The weekly preseason cycle had lower loads on Monday and Thursday whereas Tuesday and Friday produced the highest loads. The preseason described herein adopted a progressive overload comprising a weekly undulating cycle. This study emphasises how skill and games-based training contributes significantly to the overall load of a professional rugby league team's preseason with more traditional conditioning promoting high-speed running load and high metabolic load.

Research and Prospect on Key Technologies of Indoor Positioning Based on Visible Light Communication

Indoor positioning has become a research hotspot because of its important application value in industrial production and daily life. Traditional wireless positioning technologies such as Wi Fi and Bluetooth are difficult to achieve high-precision indoor positioning due to electromagnetic interference and multipath effect. The modulated white LED can not only meet the needs of lighting, but also transmit the location information to achieve high-precision indoor positioning. This paper first introduces several modulation methods commonly used in visible light positioning system, compares the characteristics of different modulation methods, and proposes a modulation method suitable for visible light positioning; Then, two demodulation methods of the visible light positioning system are introduced and discussed; After that, several visible light location algorithms are introduced, and the performance of each algorithm is analyzed in detail; Finally, the problems in visible light positioning are discussed and prospected.