Wireless energy harvesting using radio frequency (RF) energy is a growing area of research to power in- and/or on-body sensors. In a multiple intended RF energy source environment, where energy is harvested using the harvest-then-transmit protocol, this thesis tackles the problem of optimizing system timings to simultaneously maximize the harvested energy and system-level achievable data rate by using optimization theory and source selection algorithms. The possibility of energy harvesting using pure unintended RF was also explored. Although it was found that pure unintended RF energy harvesting is probably infeasible, adding additional intended RF sources can increase the achievable data rate by up to 38% and reduce the standard deviation of data rate between sensor nodes by up to 64.5%. The findings open the door for further research in powering future generation in- and/or on-body sensors efficiently using energy from multiple intended RF sources.