The rise of heterogeneity in wireless technologies operating in the 
unlicensed bands has been shown to adversely affect the performance of 
low-power wireless networks. Cross Technology Interference (CTI) is highly 
uncertain and raises the need for agile methods that assess the channel 
conditions and apply actions maximizing communication success. In this paper, 
we present TIIM, a lightweight Technology-Independent Interference Mitigation 
solution that detects, quantifies, and reacts to CTI in realtime. TIIM employs 
a lightweight machine learning classifier to (i) decide whether communication 
is viable over the interfered link, (ii) characterize the ambient conditions 
and apply the best coexistence mitigation strategy. We present an in-depth 
experimental characterization of the effect of CTI on 802.15.4 links, which 
motivated and influenced the design of TIIM. Our evaluation shows that TIIM, 
while exposed to extensive and heterogeneous interference, can achieve a total 
PRR improvement of 30% with an additional transmission overhead of 5.6%.