Wisconsin is the largest producer of Cranberries in the United States with 5.6 million barrels produced in 2017. To date, Precision Agriculture technologies adapted to cranberry production have been limited. The objective of this research was to assess the feasibility of the use of commercial remote sensing devices and Unmanned Aerial Systems in cranberry production. Two commercially available sensors were assessed for use in cranberry production: 1) MicaSense Red Edge and 2) Zenmuse XT. Initial investigation assessed the cranberry beds during the growing season. Multi-spectral remote sensing and vegetative index images have previously been used to identify regions within the cranberry beds where fertilizer deficiencies exist and the presence of pest damage. Images were collected bi-weekly during the growing season and variations in vegetative indices were successfully detected within the beds. These could be attributed to fertilizer deficiencies or other potential issues within the bed. Further ground truthing of the data is required. Continuation of this research is currently underway to utilize the combination of the above remote sensing technologies to detect regions within the cranberry beds infested by cranberry insect pests. A replicated trial was conducted by introducing sparganothis fruitworm (Sparganothis sulfureana Clemens)and fall armyworm (Spodoptera frugiperda Smith) larvae onto cranberry plants in a greenhouse setting. Multi-spectral and thermal images of the damaged cranberry plants were collected weekly. Results showed Normalized Difference Vegetative Index values decreased as insect damage increased. The vegetative index values were shown to increase again as the plants grew and more biomass was present. Larvae density was not sufficiently high to cause noticeable increases in temperature of the plants. Field scale assessment of these technologies will be conducted during the 2018 growing season.