Today, large companies specialized in forestry or park maintenance may own very large machine fleets consisting of hundreds of trimmers, chainsaws and brush cutters. Husqvarna Group, whose core business lies within high-end forestry and gardening products, has noticed that such companies tend to buy cheaper, low quality forestry and gardening products. The reason is thought to be that the companies lack a proper overview of the service status and utilization levels of their machines, leading to insufficient service, causing machines to break prematurely and making it hard to motivate investments in more expensive products. Hence, the companies usually adopt a consumerist approach, and buy cheaper products that are thrown away upon breaking. To make their products more attractive to machine park owners, Husqvarna want to explore the area of Internet of Things and equip their machines with sensing and communication capabilities. Collected data could be used to provide an overview of machine usage and service requirements to the machine parks owners, and could make it easier for machine park owners to dimension their machine fleet. In addition to this, a machine monitoring system where specific operator behavior can be tracked could enable identification of operators who consistently mistreat their machines by, for example, running the machine engine at non-optimal rotation speeds. In this master's thesis, a demonstrator of the working principle of a Bluetooth Low Energy based Fleet Service System is designed and implemented, complete with an evaluation of if received signal strength indicator (RSSI) is a good enough distance estimator to determine which operator operates a certain machine. Experiments carried out indicate that while RSSI is not a good estimator of distance, it could be used to determine the operator in closest proximity given that operators are not allowed to work closer than within a 10 m radius of each other.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-304787 |
| Date | January 2016 |
| Creators | Amanda, Nordhamn |
| Publisher | Uppsala universitet, Datorteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | UPTEC F, 1401-5757 ; 16057 |
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