IoT-Driven Workflows for Risk Management and Control of Beehives

Abstract

The internet of things (IoT) and Industry 4.0 technologies are becoming widely used in the field of apiculture to enhance honey production and reduce colony losses using connected scales combined with additional data, such as relative humidity and internal temperature. This paper exploits beehive weight measurements and builds appropriate business rules using two instruments. The first is an IoT fixed scale installed on one hive, taking rich continuous measurements, and used as a reference. The second is a portable nomad scale communicating with a smartphone and used for the remaining hives. A key contribution will be the run and triggering of a business process model based on apicultural business rules learned from experience and system observed events. Later, the evolution of the weight of each individual hive, obtained by either measurement or inference, will be associated with a graphical workflow diagram expressed with the business process model and notation (BPMN) language, and will trigger events that inform beekeepers to initiate relevant action. Finally, the BPMN processes will be transformed into executable models for model driven decision support. This contribution improves amateur and professional user-experience for honeybee keeping and opens the door for interoperability between the suggested model and other available simulations (weather, humidity, bee colony behavior, etc.).

Addressing Business Process Deviations through the Evaluation of Alternative Pattern-Based Models

“…In order to showcase the proposed approach and to demonstrate how fast the elimination of non-compatible patterns can be, the authors selected a piece of honeybee BPMN model developed with help of amateur and professional beekeepers in Lebanon and France, and well discussed in a previous publication from the same authors [16]. Before establishing the proof of concept for the bee hibernation model, the working environment was set up to interface with an existing BPMN model and process its tasks.…”

“…Although, detecting deviations is not the subject of this study, and in this paper, it is supposed that an anomaly detection has been flagged and a repairing mechanism is proposed, numerous studies, and organizations such as Airbus have focused on the aspect of problem identification in the One-Way project [14], which established a Numerical Twin to identify any deviations in a system from its intended behaviour, whereas other studies have considered artificial intelligence (AI) to improve the system's ability to identify and describe systematic deviations present in data and models [15,16]. Hodge et al [17] outlined numerous methods for detecting deviations.…”

Swarm Intelligence to Face IoT Challenges

“…Te Internet of Tings has transformed the traditional way of life into a modern one. Smart cities [12][13][14], smart homes [15,16], smart health [17][18][19], smart industries [20], smart transportation [21,22], agriculture [23,24], energy saving [25], and pollution control [26] are such transformations due to IoT. Several important research projects and studies have been carried out in an efort to advance technology through IoT.…”

Smartphone Security and Privacy: A Survey on APTs, Sensor-Based Attacks, Side-Channel Attacks, Google Play Attacks, and Defenses

“…Most of the time, such kinds of APT are launched to spy and target high profiles, government/ private institutions, surveillance agencies, as well as common users. Mostly, the purpose of these attacks is to spy on target activities by stealing device data, such as call logs, contacts, images, videos, and documents [11,12].…”