Visual SLAM for Indoor Livestock and Farming Using a Small Drone with a Monocular Camera: A Feasibility Study

Krul, Sander; Pantos, Christos; Frangulea, Mihai; Valente, João

doi:10.3390/drones5020041

Cited by 54 publications

(29 citation statements)

References 54 publications

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“…The work in [30] investigated the feasibility of utilizing small commercial drones for indoor livestock monitoring. As a GPS signal is unavailable in indoor scenarios, the performance of visual simultaneous localization and mapping (VSLAM) algorithms was examined.…”

Section: Uav Applications In Smart Farmingmentioning

confidence: 99%

LoRa Communications as an Enabler for Internet of Drones towards Large-Scale Livestock Monitoring in Rural Farms

Behjati

Noh

Alobaidy

et al. 2021

Sensors

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Currently, smart farming is considered an effective solution to enhance the productivity of farms; thereby, it has recently received broad interest from service providers to offer a wide range of applications, from pest identification to asset monitoring. Although the emergence of digital technologies, such as the Internet of Things (IoT) and low-power wide-area networks (LPWANs), has led to significant advances in the smart farming industry, farming operations still need more efficient solutions. On the other hand, the utilization of unmanned aerial vehicles (UAVs), also known as drones, is growing rapidly across many civil application domains. This paper aims to develop a farm monitoring system that incorporates UAV, LPWAN, and IoT technologies to transform the current farm management approach and aid farmers in obtaining actionable data from their farm operations. In this regard, an IoT-based water quality monitoring system was developed because water is an essential aspect in livestock development. Then, based on the Long-Range Wide-Area Network (LoRaWAN®) technology, a multi-channel LoRaWAN® gateway was developed and integrated into a vertical takeoff and landing drone to convey collected data from the sensors to the cloud for further analysis. In addition, to develop LoRaWAN®-based aerial communication, a series of measurements and simulations were performed under different configurations and scenarios. Finally, to enhance the efficiency of aerial-based data collection, the UAV path planning was optimized. Measurement results showed that the maximum achievable LoRa coverage when operating on-air via the drone is about 10 km, and the Longley–Rice irregular terrain model provides the most suitable path loss model for the scenario of large-scale farms, and a multi-channel gateway with a spreading factor of 12 provides the most reliable communication link at a high drone speed (up to 95 km/h). Simulation results showed that the developed system can overcome the coverage limitation of LoRaWAN® and it can establish a reliable communication link over large-scale wireless sensor networks. In addition, it was shown that by optimizing flight paths, aerial data collection could be performed in a much shorter time than industrial mission planning (up to four times in our case).

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Section: Uav Applications In Smart Farmingmentioning

confidence: 99%

LoRa Communications as an Enabler for Internet of Drones towards Large-Scale Livestock Monitoring in Rural Farms

Behjati

Noh

Alobaidy

et al. 2021

Sensors

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“…Technological advances have led to the increased use of unmanned aerial vehicles (UAVs), or drones, for multiple roles in agriculture. These uses range from moving livestock [25] and spraying weeds to data monitoring [26] and data gathering, such as monitoring crop health [27]. With drones starting to be used in audits in general, there is also the potential to use them in on-farm audits.…”

Section: Hybrid and Remote Auditingmentioning

confidence: 99%

Trusting in the “Eye in the Sky”? Farmers’ and Auditors’ Perceptions of Drone Use in Environmental Auditing

Lucock

Westbrooke

2021

Sustainability

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Worldwide, the agricultural sector is under pressure to demonstrate environmental sustainability. In New Zealand, farm environment plans (FEPs) and their auditing were intended to guide farmers towards sustainable practices by meeting regulations. However, on-farm audits can be time consuming, costly, and stressful for farmers. Meanwhile, the advancement of drone technology has made it possible to incorporate such tools in environmental audits. By means of field observation and in-depth interviews with both farmers and auditors, this research investigated the processes and perceptions of incorporating drones in environmental audits. The aerial views provided additional, high-quality information for the audit. However, flying a drone is subject to weather conditions. Additionally, reductions in audit time were dependent on farm scale, topography, and the auditor’s knowledge of the farm and the farmer. Farmer-auditor relationships are critical for enabling the benefits of drone use within the FEP audit process. Such relationships require a high level of interaction-based trust between farmers and auditors. Further clarity around the use and ownership of drone images could enhance trust, enabling the benefits of drones in audits to be fully utilised, hence furthering the environmental management and compliance processes towards achieving their objectives of better environmental outcomes.

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“…In indoor environments that are frequently GNSS unavailable, simultaneous localization and mapping (SLAM) [18] are used widely for localization and tracking of drones [19,20]. In recent years, environmental mapping and location identification have been actualized from visual SLAM [21][22][23][24] using depth cameras and light detection and ranging (LiDAR) sensors [25]. Numerous visual SLAM-based methods have been proposed [26], not only for research purposes but also for practical applications such as floor-cleaning robots [27].…”

Section: Introductionmentioning

confidence: 99%

Prototype Development of Cross-Shaped Microphone Array System for Drone Localization Based on Delay-and-Sum Beamforming in GNSS-Denied Areas

Madokoro

Yamamoto

Watanabe

et al. 2021

Drones

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Drones equipped with a global navigation satellite system (GNSS) receiver for absolute localization provide high-precision autonomous flight and hovering. However, the GNSS signal reception sensitivity is considerably lower in areas such as those between high-rise buildings, under bridges, and in tunnels. This paper presents a drone localization method based on acoustic information using a microphone array in GNSS-denied areas. Our originally developed microphone array system comprised 32 microphones installed in a cross-shaped configuration. Using drones of two different sizes and weights, we obtained an original acoustic outdoor benchmark dataset at 24 points. The experimentally obtained results revealed that the localization error values were lower for 0∘ and ±45∘ than for ±90∘. Moreover, we demonstrated the relative accuracy for acceptable ranges of tolerance for the obtained localization error values.

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Visual SLAM for Indoor Livestock and Farming Using a Small Drone with a Monocular Camera: A Feasibility Study

Cited by 54 publications

References 54 publications

LoRa Communications as an Enabler for Internet of Drones towards Large-Scale Livestock Monitoring in Rural Farms

LoRa Communications as an Enabler for Internet of Drones towards Large-Scale Livestock Monitoring in Rural Farms

Trusting in the “Eye in the Sky”? Farmers’ and Auditors’ Perceptions of Drone Use in Environmental Auditing

Prototype Development of Cross-Shaped Microphone Array System for Drone Localization Based on Delay-and-Sum Beamforming in GNSS-Denied Areas

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